Unverified Commit 7d50244e authored by Illia Silin's avatar Illia Silin Committed by GitHub
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Merge pull request #209 from ROCm/andriy/merge_from_public

Update develop branch from public repository
parents f221c2b0 d51701d4
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core/config.hpp"
#include "ck_tile/core/container/multi_index.hpp"
#include "ck_tile/core/container/container_helper.hpp"
#include "ck_tile/core/utility/functional.hpp"
#include "ck_tile/core/utility/type_traits.hpp"
namespace ck_tile {
// pre-defined indexing adaptor used for indexing(scatter/gather)
// this version cache the index inside thread register(which is also prefered in real senario)
// however it's user's responsibility that each thread only provide one indexing, which means
// move coordinate will not change on this dim
template <typename IndexingType>
struct indexing_adaptor_onshot_cached
{
CK_TILE_HOST_DEVICE constexpr indexing_adaptor_onshot_cached() = default;
CK_TILE_HOST_DEVICE constexpr indexing_adaptor_onshot_cached(const IndexingType& idx)
: cached_idx_(idx)
{
}
IndexingType cached_idx_;
template <typename LowIdx, typename UpIdx>
CK_TILE_HOST_DEVICE constexpr void calculate_lower_index(LowIdx& idx_low,
const UpIdx& /*idx_up*/) const
{
static_assert(LowIdx::size() == 1 && UpIdx::size() == 1,
"wrong! inconsistent # of dimension");
idx_low(number<0>{}) = cached_idx_;
}
template <typename LowIdxDiff, typename UpIdxDiff, typename LowIdx, typename UpIdx>
CK_TILE_HOST_DEVICE void update_lower_index(LowIdxDiff& idx_diff_low,
const UpIdxDiff& idx_diff_up,
LowIdx& /*idx_low*/,
const UpIdx& /*idx_up*/) const
{
// TODO: nonthing changed here
static_assert(LowIdxDiff::size() == 1 && UpIdxDiff::size() == 1 && LowIdx::size() == 1 &&
UpIdx::size() == 1,
"wrong! inconsistent # of dimension");
idx_diff_low(number<0>{}) = idx_diff_up[number<0>{}];
// pass the diff to lower, but not changing the actually index
}
CK_TILE_HOST_DEVICE static constexpr bool is_known_at_compile_time()
{
return ck_tile::is_known_at_compile_time<IndexingType>::value;
}
};
} // namespace ck_tile
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -81,8 +81,10 @@ struct space_filling_curve
return get_step_between(number<AccessIdx1d>{}, number<AccessIdx1d - 1>{});
}
// Do not use this function directly!
// TODO: can refactor into generic lambda in the future
template <index_t AccessIdx1d>
static CK_TILE_HOST_DEVICE constexpr Index get_index(number<AccessIdx1d>)
static CK_TILE_HOST_DEVICE constexpr Index _get_index(number<AccessIdx1d>)
{
#if 0
/*
......@@ -153,11 +155,11 @@ struct space_filling_curve
return idx_md;
}
// FIXME: rename this function
// FIXME: return tuple of number<>, which is compile time only variable
template <index_t AccessIdx1d>
static CK_TILE_HOST_DEVICE constexpr auto get_index_tuple_of_number(number<AccessIdx1d>)
static CK_TILE_HOST_DEVICE constexpr auto get_index(number<AccessIdx1d>)
{
constexpr auto idx = get_index(number<AccessIdx1d>{});
constexpr auto idx = _get_index(number<AccessIdx1d>{});
return generate_tuple([&](auto i) { return number<idx[i]>{}; }, number<nDim>{});
}
......
......@@ -621,6 +621,99 @@ CK_TILE_DEVICE void buffer_load_fence(index_t cnt = 0)
asm volatile("s_waitcnt vmcnt(%0)" : : "n"(cnt) : "memory");
}
namespace impl {
// below type indicate the data type used for buffer load inline asm
// clang-format off
template<index_t N, typename T> struct smem_load_trait;
template<typename T> struct smem_load_trait<16, T> { using payload_t = fp32x4_t; };
template<typename T> struct smem_load_trait<8 , T> { using payload_t = fp32x2_t; };
template<typename T> struct smem_load_trait<4 , T> { using payload_t = float; };
template<typename T> struct smem_load_trait<2 , T> { using payload_t = float; };
template<typename T> struct smem_load_trait<1 , T> { using payload_t = float; };
// clang-format on
} // namespace impl
// NOTE: smem load/store no need pre_nop to make sure dependency by sw, happy :)
template <index_t>
struct smem_load;
template <>
struct smem_load<16>
{
template <typename T>
CK_TILE_DEVICE void operator()(T& value, index_t v_offset, index_t i_offset)
{
static_assert(sizeof(T) == 16);
using mbuf_t = typename impl::smem_load_trait<16, T>::payload_t;
asm volatile("ds_read_b128 %0, %1 offset:%2"
: "=v"(reinterpret_cast<mbuf_t&>(value)) // ! direct write
: "v"(v_offset), "n"(i_offset)
: "memory");
}
};
template <>
struct smem_load<8>
{
template <typename T>
CK_TILE_DEVICE void operator()(T& value, index_t v_offset, index_t i_offset)
{
static_assert(sizeof(T) == 8);
using mbuf_t = typename impl::smem_load_trait<8, T>::payload_t;
asm volatile("ds_read_b64 %0, %1 offset:%2"
: "=v"(reinterpret_cast<mbuf_t&>(value)) // ! direct write
: "v"(v_offset), "n"(i_offset)
: "memory");
}
};
template <>
struct smem_load<4>
{
template <typename T>
CK_TILE_DEVICE void operator()(T& value, index_t v_offset, index_t i_offset)
{
static_assert(sizeof(T) == 4);
using mbuf_t = typename impl::smem_load_trait<4, T>::payload_t;
asm volatile("ds_read_b32 %0, %1 offset:%2"
: "=v"(reinterpret_cast<mbuf_t&>(value)) // ! direct write
: "v"(v_offset), "n"(i_offset)
: "memory");
}
};
template <>
struct smem_load<2>
{
template <typename T>
CK_TILE_DEVICE void operator()(T& value, index_t v_offset, index_t i_offset)
{
static_assert(sizeof(T) == 4); // subdword is buggy, use dword buf and convert manually
using mbuf_t = typename impl::smem_load_trait<1, T>::payload_t;
asm volatile("ds_read_u16 %0, %1 offset:%2"
: "=v"(reinterpret_cast<mbuf_t&>(value)) // ! direct write
: "v"(v_offset), "n"(i_offset)
: "memory");
}
};
template <>
struct smem_load<1>
{
template <typename T>
CK_TILE_DEVICE void operator()(T& value, index_t v_offset, index_t i_offset)
{
static_assert(sizeof(T) == 4);
using mbuf_t = typename impl::smem_load_trait<1, T>::payload_t;
asm volatile("ds_read_u8 %0, %1 offset:%2"
: "=v"(reinterpret_cast<mbuf_t&>(value)) // ! direct write
: "v"(v_offset), "n"(i_offset)
: "memory");
}
};
// clang-format off
namespace impl{
......@@ -976,6 +1069,16 @@ llvm_amdgcn_raw_buffer_atomic_max_fp64(double vdata,
int soffset, // dst_wave_addr_offset
int glc_slc) __asm("llvm.amdgcn.raw.buffer.atomic.fmax.f64");
// Direct loads from global to LDS.
CK_TILE_DEVICE_EXTERN void
llvm_amdgcn_raw_buffer_load_lds(int32x4_t rsrc,
__attribute__((address_space(3))) uint32_t* lds_ptr,
index_t size,
index_t voffset,
index_t soffset,
index_t offset,
index_t aux) __asm("llvm.amdgcn.raw.buffer.load.lds");
template <bool pre_nop = false>
CK_TILE_DEVICE void async_buffer_load_dword_v(void* smem,
int32x4_t rsrc,
......@@ -1313,6 +1416,7 @@ CK_TILE_DEVICE void amd_buffer_load_raw_impl(thread_buffer<T, N>& dst,
int32x4_t src_wave_buffer_resource,
index_t src_thread_addr_offset,
index_t src_wave_addr_offset,
index_t src_linear_addr_offset,
index_t flag = 0,
bool_constant<pre_nop> = {})
{
......@@ -1327,7 +1431,7 @@ CK_TILE_DEVICE void amd_buffer_load_raw_impl(thread_buffer<T, N>& dst,
src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset,
0,
src_linear_addr_offset,
flag,
bool_constant<pre_nop>{});
}
......@@ -1337,7 +1441,7 @@ CK_TILE_DEVICE void amd_buffer_load_raw_impl(thread_buffer<T, N>& dst,
src_wave_buffer_resource,
src_thread_addr_offset,
src_wave_addr_offset,
0,
src_linear_addr_offset,
flag,
bool_constant<pre_nop>{});
}
......@@ -1365,6 +1469,43 @@ CK_TILE_DEVICE void amd_async_buffer_load_impl(T* smem,
bool_constant<pre_nop>{});
}
template <typename T,
index_t N,
amd_buffer_coherence_enum coherence = amd_buffer_coherence_enum::coherence_default,
bool oob_conditional_check = true>
CK_TILE_DEVICE void amd_async_buffer_load(CK_TILE_LDS_ADDR T* smem,
int32x4_t src_wave_buffer_resource,
index_t src_thread_addr_offset,
index_t src_wave_addr_offset,
index_t src_immediate_addr_offset = 0,
index_t flag = 0,
bool_constant<oob_conditional_check> = {})
{
static_assert(sizeof(T) * N == 4, "wrong! not implemented vector size");
if constexpr(oob_conditional_check)
{
index_t v_offset = flag ? v_offset : src_wave_buffer_resource[2];
llvm_amdgcn_raw_buffer_load_lds(src_wave_buffer_resource,
smem,
sizeof(uint32_t),
v_offset,
src_wave_addr_offset,
src_immediate_addr_offset,
static_cast<index_t>(coherence));
}
else
{
llvm_amdgcn_raw_buffer_load_lds(src_wave_buffer_resource,
smem,
sizeof(uint32_t),
src_thread_addr_offset,
src_wave_addr_offset,
src_immediate_addr_offset,
static_cast<index_t>(coherence));
}
}
template <index_t N,
amd_buffer_coherence_enum coherence = amd_buffer_coherence_enum::coherence_default>
CK_TILE_DEVICE void amd_buffer_store_impl_with_bytes(const thread_buffer<int8_t, N> src_thread_data,
......@@ -1685,6 +1826,7 @@ CK_TILE_DEVICE void amd_buffer_store_raw_impl(const thread_buffer<T, N>& dst_thr
int32x4_t dst_wave_buffer_resource,
index_t dst_thread_addr_offset,
index_t dst_wave_addr_offset,
index_t dst_linear_addr_offset,
index_t is_valid_element = 1)
{
constexpr index_t bytes = sizeof(T) * N;
......@@ -1698,7 +1840,7 @@ CK_TILE_DEVICE void amd_buffer_store_raw_impl(const thread_buffer<T, N>& dst_thr
dst_wave_buffer_resource,
dst_thread_addr_offset,
dst_wave_addr_offset,
0,
dst_linear_addr_offset,
is_valid_element);
}
else
......@@ -1707,7 +1849,7 @@ CK_TILE_DEVICE void amd_buffer_store_raw_impl(const thread_buffer<T, N>& dst_thr
dst_wave_buffer_resource,
dst_thread_addr_offset,
dst_wave_addr_offset,
0);
dst_linear_addr_offset);
}
}
......@@ -2014,6 +2156,7 @@ template <typename T,
CK_TILE_DEVICE void amd_buffer_load_raw(thread_buffer<T, N>& dst,
const T* p_src_wave,
index_t src_thread_element_offset,
index_t src_linear_element_offset,
index_t src_element_space_size,
index_t is_valid_element = 0,
bool_constant<pre_nop> = {})
......@@ -2022,12 +2165,14 @@ CK_TILE_DEVICE void amd_buffer_load_raw(thread_buffer<T, N>& dst,
make_wave_buffer_resource(p_src_wave, src_element_space_size * sizeof(T));
index_t src_thread_addr_offset = src_thread_element_offset * sizeof(T);
index_t src_linear_addr_offset = src_linear_element_offset * sizeof(T);
amd_buffer_load_raw_impl<T, N, coherence, oob_conditional_check, pre_nop>(
dst,
src_wave_buffer_resource,
src_thread_addr_offset,
0,
src_linear_addr_offset,
is_valid_element,
bool_constant<pre_nop>{});
}
......@@ -2041,16 +2186,19 @@ template <typename T,
CK_TILE_DEVICE void amd_buffer_load_raw(thread_buffer<T, N>& dst,
const int32x4_t src_wave_buffer_resource,
index_t src_thread_element_offset,
index_t src_linear_element_offset,
index_t is_valid_element = 0,
bool_constant<pre_nop> = {})
{
index_t src_thread_addr_offset = src_thread_element_offset * sizeof(T);
index_t src_linear_addr_offset = src_linear_element_offset * sizeof(T);
amd_buffer_load_raw_impl<T, N, coherence, oob_conditional_check, pre_nop>(
dst,
src_wave_buffer_resource,
src_thread_addr_offset,
0,
src_linear_addr_offset,
is_valid_element,
bool_constant<pre_nop>{});
}
......@@ -2066,6 +2214,7 @@ template <typename T,
CK_TILE_DEVICE void amd_async_buffer_load_with_oob_raw(T* smem,
const T* p_src_wave,
index_t src_thread_element_offset,
index_t src_linear_element_offset,
index_t src_element_space_size,
bool_constant<pre_nop> = {})
{
......@@ -2073,9 +2222,14 @@ CK_TILE_DEVICE void amd_async_buffer_load_with_oob_raw(T* smem,
make_wave_buffer_resource(p_src_wave, src_element_space_size * sizeof(T));
index_t src_thread_addr_offset = src_thread_element_offset * sizeof(T);
index_t src_linear_addr_offset = src_linear_element_offset * sizeof(T);
amd_async_buffer_load_impl<T, N, coherence>(
smem, src_wave_buffer_resource, src_thread_addr_offset, 0, 0, bool_constant<pre_nop>{});
amd_async_buffer_load_impl<T, N, coherence>(smem,
src_wave_buffer_resource,
src_thread_addr_offset,
0,
src_linear_addr_offset,
bool_constant<pre_nop>{});
}
// This version support buffer resource as input arg
......@@ -2086,12 +2240,42 @@ template <typename T,
CK_TILE_DEVICE void amd_async_buffer_load_with_oob_raw(T* smem,
const int32x4_t src_wave_buffer_resource,
index_t src_thread_element_offset,
index_t src_linear_element_offset,
bool_constant<pre_nop> = {})
{
index_t src_thread_addr_offset = src_thread_element_offset * sizeof(T);
index_t src_linear_addr_offset = src_linear_element_offset * sizeof(T);
amd_async_buffer_load_impl<T, N, coherence>(
smem, src_wave_buffer_resource, src_thread_addr_offset, 0, 0, bool_constant<pre_nop>{});
amd_async_buffer_load_impl<T, N, coherence>(smem,
src_wave_buffer_resource,
src_thread_addr_offset,
0,
src_linear_addr_offset,
bool_constant<pre_nop>{});
}
// This version support buffer resource as input arg
template <typename T,
index_t N,
amd_buffer_coherence_enum coherence = amd_buffer_coherence_enum::coherence_default,
bool oob_conditional_check = false>
CK_TILE_DEVICE void amd_async_buffer_load_with_oob(CK_TILE_LDS_ADDR T* smem,
const int32x4_t src_wave_buffer_resource,
index_t src_thread_element_offset,
index_t src_linear_element_offset,
bool is_valid_element,
bool_constant<oob_conditional_check> = {})
{
index_t src_thread_addr_offset = src_thread_element_offset * sizeof(T);
index_t src_linear_addr_offset = src_linear_element_offset * sizeof(T);
amd_async_buffer_load<T, N, coherence>(smem,
src_wave_buffer_resource,
src_thread_addr_offset,
0,
src_linear_addr_offset,
is_valid_element,
bool_constant<oob_conditional_check>{});
}
// buffer_store requires:
......@@ -2146,6 +2330,7 @@ template <typename T,
CK_TILE_DEVICE void amd_buffer_store_raw(const thread_buffer<T, N>& src_thread_data,
T* p_dst_wave,
const index_t dst_thread_element_offset,
const index_t dst_linear_element_offset,
const bool dst_thread_element_valid,
const index_t dst_element_space_size)
{
......@@ -2153,11 +2338,13 @@ CK_TILE_DEVICE void amd_buffer_store_raw(const thread_buffer<T, N>& src_thread_d
make_wave_buffer_resource(p_dst_wave, dst_element_space_size * sizeof(T));
index_t dst_thread_addr_offset = dst_thread_element_offset * sizeof(T);
index_t dst_linear_addr_offset = dst_linear_element_offset * sizeof(T);
amd_buffer_store_raw_impl<T, N, coherence, oob_conditional_check>(src_thread_data,
dst_wave_buffer_resource,
dst_thread_addr_offset,
0,
dst_linear_addr_offset,
dst_thread_element_valid);
}
......@@ -2221,16 +2408,6 @@ CK_TILE_DEVICE void amd_buffer_atomic_max(const thread_buffer<T, N>& src_thread_
#endif
}
// Direct loads from global to LDS.
CK_TILE_DEVICE_EXTERN void
llvm_amdgcn_raw_buffer_load_lds(int32x4_t rsrc,
__attribute__((address_space(3))) uint32_t* lds_ptr,
index_t size,
index_t voffset,
index_t soffset,
index_t offset,
index_t aux) __asm("llvm.amdgcn.raw.buffer.load.lds");
template <typename T, index_t NumElemsPerThread>
CK_TILE_DEVICE void amd_direct_load_global_to_lds(const T* global_base_ptr,
const index_t global_offset,
......
......@@ -41,6 +41,19 @@
#define CK_TILE_HOST_DEVICE_EXTERN
#endif
// implementing the "memory address space" attribute
// https://llvm.org/docs/AMDGPUUsage.html#amdgpu-address-spaces-table
#ifdef __HIPCC_
#define CK_TILE_GENERIC_ADDR __attribute__((address_space(0)))
#define CK_TILE_GLOBAL_ADDR __attribute__((address_space(1)))
#define CK_TILE_LDS_ADDR __attribute__((address_space(3)))
#define CK_TILE_BUF_RES_ADDR __attribute__((address_space(8)))
#else
#define CK_TILE_GENERIC_ADDR
#define CK_TILE_GLOBAL_ADDR
#define CK_TILE_LDS_ADDR
#define CK_TILE_BUF_RES_ADDR
#endif
#ifndef CK_TILE_USE_CUSTOM_DATA_TYPE
#define CK_TILE_USE_CUSTOM_DATA_TYPE 0 // custom data type will generate extra move/bfi code
#endif
......@@ -205,3 +218,8 @@
#ifndef CK_TILE_BUFFER_LOAD_RAW_BF16_WA
#define CK_TILE_BUFFER_LOAD_RAW_BF16_WA 1
#endif
// workaround: compiler not emiting reciprocal instruction frm __frcp_rn()
#ifndef CK_TILE_WORKAROUND_SWDEV_383542
#define CK_TILE_WORKAROUND_SWDEV_383542 1
#endif
......@@ -623,7 +623,7 @@ template <typename... Ys,
false>
CK_TILE_HOST_DEVICE constexpr auto operator+=(tuple<Ys...>& y, const X& x)
{
static_assert(X::Size() == sizeof...(Ys), "wrong! size not the same");
static_assert(X::size() == sizeof...(Ys), "wrong! size not the same");
constexpr index_t NSize = sizeof...(Ys);
static_for<0, NSize, 1>{}([&](auto i) { y[i] += x[i]; });
return y;
......@@ -635,7 +635,7 @@ template <typename... Ys,
false>
CK_TILE_HOST_DEVICE constexpr auto operator-=(tuple<Ys...>& y, const X& x)
{
static_assert(X::Size() == sizeof...(Ys), "wrong! size not the same");
static_assert(X::size() == sizeof...(Ys), "wrong! size not the same");
constexpr index_t NSize = sizeof...(Ys);
static_for<0, NSize, 1>{}([&](auto i) { y[i] -= x[i]; });
return y;
......@@ -647,7 +647,7 @@ template <typename... Xs,
false>
CK_TILE_HOST_DEVICE constexpr auto operator+(const tuple<Xs...>& x, const Y& y)
{
static_assert(Y::Size() == sizeof...(Xs), "wrong! size not the same");
static_assert(Y::size() == sizeof...(Xs), "wrong! size not the same");
constexpr index_t NSize = sizeof...(Xs);
tuple<Xs...> r;
......@@ -655,13 +655,21 @@ CK_TILE_HOST_DEVICE constexpr auto operator+(const tuple<Xs...>& x, const Y& y)
return r;
}
template <typename... Xs, typename... Ys>
CK_TILE_HOST_DEVICE constexpr auto operator+(const tuple<Xs...>& x, const tuple<Ys...>& y)
{
static_assert(sizeof...(Xs) == sizeof...(Ys), "wrong!");
constexpr index_t NSize = sizeof...(Xs);
return generate_tuple([&](auto i) { return x[i] + y[i]; }, number<NSize>{});
}
template <typename... Xs,
typename Y,
std::enable_if_t<!std::is_integral<Y>::value && !std::is_floating_point<Y>::value, bool> =
false>
CK_TILE_HOST_DEVICE constexpr auto operator-(const tuple<Xs...>& x, const Y& y)
{
static_assert(Y::Size() == sizeof...(Xs), "wrong! size not the same");
static_assert(Y::size() == sizeof...(Xs), "wrong! size not the same");
constexpr index_t NSize = sizeof...(Xs);
tuple<Xs...> r;
......@@ -669,13 +677,21 @@ CK_TILE_HOST_DEVICE constexpr auto operator-(const tuple<Xs...>& x, const Y& y)
return r;
}
template <typename... Xs, typename... Ys>
CK_TILE_HOST_DEVICE constexpr auto operator-(const tuple<Xs...>& x, const tuple<Ys...>& y)
{
static_assert(sizeof...(Xs) == sizeof...(Ys), "wrong!");
constexpr index_t NSize = sizeof...(Xs);
return generate_tuple([&](auto i) { return x[i] - y[i]; }, number<NSize>{});
}
template <typename... Xs,
typename Y,
std::enable_if_t<!std::is_integral<Y>::value && !std::is_floating_point<Y>::value, bool> =
false>
CK_TILE_HOST_DEVICE constexpr auto operator*(const tuple<Xs...>& x, const Y& y)
{
static_assert(Y::Size() == sizeof...(Xs), "wrong! size not the same");
static_assert(Y::size() == sizeof...(Xs), "wrong! size not the same");
constexpr index_t NSize = sizeof...(Xs);
tuple<Xs...> r;
......@@ -706,6 +722,14 @@ CK_TILE_HOST_DEVICE constexpr auto operator*(const tuple<Xs...>& x, Y a)
return a * x;
}
template <typename... Xs, typename... Ys>
CK_TILE_HOST_DEVICE constexpr auto operator*(const tuple<Xs...>& x, const tuple<Ys...>& y)
{
static_assert(sizeof...(Xs) == sizeof...(Ys), "wrong!");
constexpr index_t NSize = sizeof...(Xs);
return generate_tuple([&](auto i) { return x[i] * y[i]; }, number<NSize>{});
}
template <typename... Xs, typename... Ys>
CK_TILE_HOST_DEVICE constexpr auto operator/(const tuple<Xs...>& x, const tuple<Ys...>& y)
{
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "ck_tile/core/config.hpp"
#include "ck_tile/core/numeric/half.hpp"
#include "ck_tile/core/numeric/integral_constant.hpp"
#include "ck_tile/core/numeric/math.hpp"
#include "ck_tile/core/numeric/numeric.hpp"
#include "ck_tile/core/utility/bit_cast.hpp"
#include "ck_tile/core/utility/random.hpp"
#include <stdint.h>
#include <type_traits>
#pragma once
namespace ck_tile {
// use int8_t directly for int8 arithemetic
// here one can use ck_tile::int8_t to access original int8_t
using int8_t = int8_t;
// limits
template <class T>
struct numeric;
template <>
struct numeric<int8_t>
{
// minimum finite value, or minimum positive normalized value for float
CK_TILE_HOST_DEVICE static constexpr int8_t min() { return int8_t(-128); }
// minumum finite value
CK_TILE_HOST_DEVICE static constexpr int8_t lowest() { return int8_t(-128); }
// maximum finite value
CK_TILE_HOST_DEVICE static constexpr int8_t max() { return int8_t(127); }
// difference between 1.0 and next value representable by float
CK_TILE_HOST_DEVICE static constexpr int8_t epsilon()
{
return 1; // not used
}
CK_TILE_HOST_DEVICE static constexpr int8_t round_error()
{
return 1; // not used
}
// positive infinity value
CK_TILE_HOST_DEVICE static constexpr int8_t infinity()
{
return 1; // not used
}
// quiet NaN
CK_TILE_HOST_DEVICE static constexpr int8_t quiet_NaN()
{
return 1; // not used
}
// signaling NaN
CK_TILE_HOST_DEVICE static constexpr int8_t signaling_NaN()
{
return 1; // not used
}
// smallest positive subnormal value
CK_TILE_HOST_DEVICE static constexpr int8_t denorm_min()
{
return 1; // not used
}
CK_TILE_HOST_DEVICE static constexpr int8_t zero() { return 0; }
};
#if 0
template <typename T>
struct numeric_traits;
template <>
struct numeric_traits<int8_t>
{
static constexpr int exp = 5;
static constexpr int mant = 10;
static constexpr int bias = 15;
static constexpr uint16_t nan_mask = 0x7C00;
static constexpr uint16_t head_mask = 0xFC00;
static constexpr uint16_t mant_mask = 0x3FF;
static constexpr uint16_t exp_mask = 0x1F;
static constexpr uint32_t Inf = 0x7C00;
static constexpr uint32_t NegInf = 0xFC00;
static constexpr uint32_t NaN = 0x7C01;
static constexpr uint32_t Neg0 = 0x8000;
using bitwise_type = uint16_t;
};
#endif
CK_TILE_HOST_DEVICE
constexpr float int8_to_float(const int8_t& x) { return static_cast<float>(x); }
CK_TILE_HOST_DEVICE
constexpr int8_t float_to_int8(const float& x) { return static_cast<int8_t>(x); }
} // namespace ck_tile
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -487,55 +487,12 @@ struct log2e<float>
template <typename T = double>
constexpr T log2e_v = log2e<T>::value;
// math
CK_TILE_HOST_DEVICE
float abs(const float& x)
{
union
{
float f32;
uint32_t u32;
} y;
y.f32 = x;
y.u32 = y.u32 & 0x7fffffff;
return y.f32;
}
CK_TILE_HOST_DEVICE
bool isnan(const float& x)
{
uint32_t xx = bit_cast<uint32_t>(x);
return (xx & 0x7fffffff) > 0x7F800000;
}
CK_TILE_HOST float sqrt(float x) { return std::sqrt(x); };
CK_TILE_HOST double sqrt(double x) { return std::sqrt(x); };
CK_TILE_DEVICE
float sqrt(float x) { return __builtin_amdgcn_sqrtf(x); };
CK_TILE_DEVICE
double sqrt(double x) { return __builtin_amdgcn_sqrt(x); };
CK_TILE_DEVICE
float exp(float x) { return __ocml_exp_f32(x); };
CK_TILE_HOST
float exp(float x) { return std::expf(x); }
CK_TILE_DEVICE
float exp2(float x) { return exp2f(x); };
CK_TILE_HOST
float exp2(float x) { return std::exp2f(x); };
CK_TILE_DEVICE
float log(float x) { return __logf(x); };
CK_TILE_HOST
float log(float x) { return std::logf(x); };
CK_TILE_DEVICE uint16_t sad_u16(uint16_t x, uint16_t y, uint16_t acc)
{
return __builtin_amdgcn_sad_u16(x, y, acc);
......@@ -554,4 +511,933 @@ CK_TILE_HOST uint32_t sad_u32(uint32_t x, uint32_t y, uint32_t acc)
return (x > y ? (x - y) : (y - x)) + acc;
}
///////////////////////////////////////////////////////////////
} // namespace ck_tile
// blow function need data type pre-defined
#include "ck_tile/core/numeric/half.hpp"
#include "ck_tile/core/numeric/bfloat16.hpp"
#include "ck_tile/core/numeric/float8.hpp"
#include "ck_tile/core/numeric/type_convert.hpp"
#ifndef __HIP_DEVICE_COMPILE__
#include <cmath>
#endif
namespace ck_tile {
#if CK_TILE_WORKAROUND_SWDEV_383542
extern "C" CK_TILE_DEVICE float __ocml_native_recip_f32(float);
#endif
// math functions for the host, some are implemented by calling C++ std functions
CK_TILE_HOST float abs(float x) { return std::abs(x); };
CK_TILE_HOST double abs(double x) { return std::abs(x); };
CK_TILE_HOST int8_t abs(int8_t x)
{
int8_t sgn = x >> (8 - 1);
return (x ^ sgn) - sgn;
};
CK_TILE_HOST int32_t abs(int32_t x)
{
int32_t sgn = x >> (32 - 1);
return (x ^ sgn) - sgn;
};
CK_TILE_HOST fp16_t abs(fp16_t x)
{
uint16_t xx = bit_cast<uint16_t>(x);
uint16_t abs_xx = xx & 0x7fff;
fp16_t abs_x = bit_cast<fp16_t>(abs_xx);
return abs_x;
};
#ifdef CK_TILE_EXPERIMENTAL_BIT_INT_EXTENSION_INT4
CK_TILE_HOST int4_t abs(int4_t x)
{
int4_t sgn = x >> (4 - 1);
return (x ^ sgn) - sgn;
}
#endif
CK_TILE_HOST bool isnan(float x) { return std::isnan(x); };
CK_TILE_HOST bool isnan(double x) { return std::isnan(x); };
CK_TILE_HOST bool isnan(int8_t x)
{
(void)x;
return false;
};
CK_TILE_HOST bool isnan(int32_t x)
{
(void)x;
return false;
};
CK_TILE_HOST bool isnan(fp16_t x)
{
uint16_t xx = bit_cast<uint16_t>(x);
return (xx & 0x7FFF) > 0x7C00;
};
#ifdef CK_TILE_EXPERIMENTAL_BIT_INT_EXTENSION_INT4
CK_TILE_HOST bool isnan(int4_t x)
{
(void)x;
return false;
};
#endif
CK_TILE_HOST fp16_t sqrt(fp16_t x)
{
return static_cast<fp16_t>(std::sqrt(static_cast<float>(x)));
};
CK_TILE_HOST float sqrt(float x) { return std::sqrt(x); };
CK_TILE_HOST double sqrt(double x) { return std::sqrt(x); };
template <typename T>
CK_TILE_HOST T tanh(T x)
{
return type_convert<T>(std::tanhf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float tanh<float>(float x)
{
return std::tanhf(x);
};
template <>
CK_TILE_HOST double tanh<double>(double x)
{
return std::tanh(x);
};
template <typename T>
CK_TILE_HOST T acos(T x)
{
return type_convert<T>(std::acosf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float acos<float>(float x)
{
return std::acosf(x);
};
template <>
CK_TILE_HOST double acos<double>(double x)
{
return std::acos(x);
};
template <typename T>
CK_TILE_HOST T neg(T x)
{
return type_convert<T>(-(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float neg<float>(float x)
{
return -x;
};
template <>
CK_TILE_HOST double neg<double>(double x)
{
return -x;
};
template <>
CK_TILE_HOST int32_t neg<int32_t>(int32_t x)
{
return -x;
};
template <>
CK_TILE_HOST int8_t neg<int8_t>(int8_t x)
{
return -x;
};
template <typename T>
CK_TILE_HOST T atan(T x)
{
return type_convert<T>(std::atanf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float atan<float>(float x)
{
return std::atanf(x);
};
template <>
CK_TILE_HOST double atan<double>(double x)
{
return std::atan(x);
};
template <typename T>
CK_TILE_HOST T sin(T x)
{
return type_convert<T>(std::sinf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float sin<float>(float x)
{
return std::sinf(x);
};
template <>
CK_TILE_HOST double sin<double>(double x)
{
return std::sin(x);
};
template <typename T>
CK_TILE_HOST T asin(T x)
{
return type_convert<T>(std::asinf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float asin<float>(float x)
{
return std::asinf(x);
};
template <>
CK_TILE_HOST double asin<double>(double x)
{
return std::asin(x);
};
template <typename T>
CK_TILE_HOST T asinh(T x)
{
return type_convert<T>(std::asinhf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float asinh<float>(float x)
{
return std::asinhf(x);
};
template <>
CK_TILE_HOST double asinh<double>(double x)
{
return std::asinh(x);
};
template <typename T>
CK_TILE_HOST T cos(T x)
{
return type_convert<T>(std::cosf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float cos<float>(float x)
{
return std::cosf(x);
};
template <>
CK_TILE_HOST double cos<double>(double x)
{
return std::cos(x);
};
template <typename T>
CK_TILE_HOST T acosh(T x)
{
return type_convert<T>(std::acoshf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float acosh<float>(float x)
{
return std::acoshf(x);
};
template <>
CK_TILE_HOST double acosh<double>(double x)
{
return std::acosh(x);
};
template <typename T>
CK_TILE_HOST T tan(T x)
{
return type_convert<T>(std::tanf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float tan<float>(float x)
{
return std::tanf(x);
};
template <>
CK_TILE_HOST double tan<double>(double x)
{
return std::tan(x);
};
template <typename T>
CK_TILE_HOST T atanh(T x)
{
return type_convert<T>(std::atanhf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float atanh<float>(float x)
{
return std::atanhf(x);
};
template <>
CK_TILE_HOST double atanh<double>(double x)
{
return std::atanh(x);
};
template <typename T>
CK_TILE_HOST T sinh(T x)
{
return type_convert<T>(std::sinhf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float sinh<float>(float x)
{
return std::sinhf(x);
};
template <>
CK_TILE_HOST double sinh<double>(double x)
{
return std::sinh(x);
};
template <typename T>
CK_TILE_HOST T ceil(T x)
{
return type_convert<T>(std::ceilf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float ceil<float>(float x)
{
return std::ceilf(x);
};
template <>
CK_TILE_HOST double ceil<double>(double x)
{
return std::ceil(x);
};
template <typename T>
CK_TILE_HOST T cosh(T x)
{
return type_convert<T>(std::coshf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float cosh<float>(float x)
{
return std::coshf(x);
};
template <>
CK_TILE_HOST double cosh<double>(double x)
{
return std::cosh(x);
};
template <typename T>
CK_TILE_HOST T floor(T x)
{
return type_convert<T>(std::floorf(type_convert<float>(x)));
};
template <>
CK_TILE_HOST float floor<float>(float x)
{
return std::floorf(x);
};
template <>
CK_TILE_HOST double floor<double>(double x)
{
return std::floor(x);
};
template <typename T>
CK_TILE_HOST T rcp(T x)
{
return type_convert<T>(1.f / type_convert<float>(x));
};
template <typename T>
CK_TILE_HOST T exp(T x)
{
return type_convert<T>(std::expf(type_convert<float>(x)));
}
template <>
CK_TILE_HOST float exp<float>(float x)
{
return std::expf(x);
}
template <>
CK_TILE_HOST double exp<double>(double x)
{
return std::exp(x);
}
template <typename T>
CK_TILE_HOST T log(T x)
{
return type_convert<T>(std::logf(type_convert<float>(x)));
}
template <>
CK_TILE_HOST float log<float>(float x)
{
return std::logf(x);
}
template <>
CK_TILE_HOST double log<double>(double x)
{
return std::log(x);
}
template <typename T>
CK_TILE_HOST T pow(T x, T gamma)
{
return type_convert<T>(std::powf(type_convert<float>(x), type_convert<float>(gamma)));
}
template <>
CK_TILE_HOST float pow<float>(float x, float gamma)
{
return std::powf(x, gamma);
}
template <>
CK_TILE_HOST double pow<double>(double x, double gamma)
{
return std::pow(x, gamma);
}
template <typename T>
CK_TILE_HOST T expm1(T x)
{
return type_convert<T>(std::expm1f(type_convert<float>(x)));
}
template <>
CK_TILE_HOST float expm1<float>(float x)
{
return std::expm1f(x);
}
template <>
CK_TILE_HOST double expm1<double>(double x)
{
return std::expm1(x);
}
// math functions for the HIP kernel, some are implemented by calling hip builtin functions
CK_TILE_DEVICE float abs(float x)
{
union
{
float f32;
uint32_t u32;
} y;
y.f32 = x;
y.u32 = y.u32 & 0x7fffffff;
return y.f32;
};
CK_TILE_DEVICE double abs(double x) { return ::abs(x); };
CK_TILE_DEVICE int8_t abs(int8_t x)
{
int8_t sgn = x >> (8 - 1);
return (x ^ sgn) - sgn;
};
CK_TILE_DEVICE int32_t abs(int32_t x)
{
int32_t sgn = x >> (32 - 1);
return (x ^ sgn) - sgn;
};
#ifdef CK_TILE_EXPERIMENTAL_BIT_INT_EXTENSION_INT4
CK_TILE_DEVICE int4_t abs(int4_t x)
{
int4_t sgn = x >> (4 - 1);
return (x ^ sgn) - sgn;
};
#endif
CK_TILE_DEVICE fp16_t abs(fp16_t x)
{
uint16_t xx = bit_cast<uint16_t>(x);
uint16_t abs_xx = xx & 0x7fff;
fp16_t abs_x = bit_cast<fp16_t>(abs_xx);
return abs_x;
};
CK_TILE_DEVICE bool isnan(float x) { return ::isnan(x); };
CK_TILE_DEVICE bool isnan(double x) { return ::isnan(x); };
CK_TILE_DEVICE bool isnan(int8_t x)
{
(void)x;
return false;
};
CK_TILE_DEVICE bool isnan(int32_t x)
{
(void)x;
return false;
};
#ifdef CK_TILE_EXPERIMENTAL_BIT_INT_EXTENSION_INT4
CK_TILE_DEVICE bool isnan(int4_t x)
{
(void)x;
return false;
};
#endif
CK_TILE_DEVICE bool isnan(fp16_t x)
{
uint16_t xx = bit_cast<uint16_t>(x);
return (xx & 0x7FFF) > 0x7C00;
};
CK_TILE_DEVICE fp16_t sqrt(fp16_t x)
{
return static_cast<fp16_t>(__builtin_amdgcn_sqrtf(static_cast<float>(x)));
};
CK_TILE_DEVICE float sqrt(float x) { return __builtin_amdgcn_sqrtf(x); };
CK_TILE_DEVICE double sqrt(double x) { return __builtin_amdgcn_sqrt(x); };
template <typename T>
CK_TILE_DEVICE T tanh(T x)
{
return type_convert<T>(::tanhf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float tanh<float>(float x)
{
return ::tanhf(x);
};
template <>
CK_TILE_DEVICE double tanh<double>(double x)
{
return ::tanh(x);
};
template <typename T>
CK_TILE_DEVICE T acos(T x)
{
return type_convert<T>(::acosf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float acos<float>(float x)
{
return ::acosf(x);
};
template <>
CK_TILE_DEVICE double acos<double>(double x)
{
return ::acos(x);
};
template <typename T>
CK_TILE_DEVICE T neg(T x)
{
return type_convert<T>(-(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float neg<float>(float x)
{
return -x;
};
template <>
CK_TILE_DEVICE double neg<double>(double x)
{
return -x;
};
template <>
CK_TILE_DEVICE int32_t neg<int32_t>(int32_t x)
{
return -x;
};
template <>
CK_TILE_DEVICE int8_t neg<int8_t>(int8_t x)
{
return -x;
};
template <>
CK_TILE_DEVICE fp16_t neg<fp16_t>(fp16_t x)
{
return -x;
};
template <typename T>
CK_TILE_DEVICE T atan(T x)
{
return type_convert<T>(::atanf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float atan<float>(float x)
{
return ::atanf(x);
};
template <>
CK_TILE_DEVICE double atan<double>(double x)
{
return ::atan(x);
};
template <typename T>
CK_TILE_DEVICE T sin(T x)
{
return type_convert<T>(::sinf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float sin<float>(float x)
{
return ::sinf(x);
};
template <>
CK_TILE_DEVICE double sin<double>(double x)
{
return ::sin(x);
};
template <>
CK_TILE_DEVICE fp16_t sin<fp16_t>(fp16_t x)
{
return __ocml_sin_f16(x);
};
template <typename T>
CK_TILE_DEVICE T asin(T x)
{
return type_convert<T>(::asinf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float asin<float>(float x)
{
return ::asinf(x);
};
template <>
CK_TILE_DEVICE double asin<double>(double x)
{
return ::asin(x);
};
template <typename T>
CK_TILE_DEVICE T asinh(T x)
{
return type_convert<T>(::asinhf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float asinh<float>(float x)
{
return ::asinhf(x);
};
template <>
CK_TILE_DEVICE double asinh<double>(double x)
{
return ::asinh(x);
};
template <typename T>
CK_TILE_DEVICE T acosh(T x)
{
return type_convert<T>(::acoshf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float acosh<float>(float x)
{
return ::acoshf(x);
};
template <>
CK_TILE_DEVICE double acosh<double>(double x)
{
return ::acosh(x);
};
template <typename T>
CK_TILE_DEVICE T tan(T x)
{
return type_convert<T>(::tanf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float tan<float>(float x)
{
return ::tanf(x);
};
template <>
CK_TILE_DEVICE double tan<double>(double x)
{
return ::tan(x);
};
template <typename T>
CK_TILE_DEVICE T atanh(T x)
{
return type_convert<T>(::atanhf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float atanh<float>(float x)
{
return ::atanhf(x);
};
template <>
CK_TILE_DEVICE double atanh<double>(double x)
{
return ::atanh(x);
};
template <typename T>
CK_TILE_DEVICE T sinh(T x)
{
return type_convert<T>(::sinhf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float sinh<float>(float x)
{
return ::sinhf(x);
};
template <>
CK_TILE_DEVICE double sinh<double>(double x)
{
return ::sinh(x);
};
template <typename T>
CK_TILE_DEVICE T ceil(T x)
{
return type_convert<T>(::ceilf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float ceil<float>(float x)
{
return ::ceilf(x);
};
template <>
CK_TILE_DEVICE double ceil<double>(double x)
{
return ::ceil(x);
};
template <>
CK_TILE_DEVICE fp16_t ceil<fp16_t>(fp16_t x)
{
return __ocml_ceil_f16(x);
};
template <typename T>
CK_TILE_DEVICE T cosh(T x)
{
return type_convert<T>(::coshf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float cosh<float>(float x)
{
return ::coshf(x);
};
template <>
CK_TILE_DEVICE double cosh<double>(double x)
{
return ::cosh(x);
};
template <typename T>
CK_TILE_DEVICE T floor(T x)
{
return type_convert<T>(::floorf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float floor<float>(float x)
{
return ::floorf(x);
};
template <>
CK_TILE_DEVICE double floor<double>(double x)
{
return ::floor(x);
};
template <>
CK_TILE_DEVICE fp16_t floor<fp16_t>(fp16_t x)
{
return __ocml_floor_f16(x);
};
template <typename T>
CK_TILE_DEVICE T rcp(T x)
{
#if !CK_TILE_WORKAROUND_SWDEV_383542
return __frcp_rn(x);
#else
// return __ocml_native_recip_f32(x);
return __builtin_amdgcn_rcpf(x);
#endif
};
template <typename T>
CK_TILE_DEVICE T exp(T x)
{
return type_convert<T>(__ocml_exp_f32(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE fp16_t exp<fp16_t>(fp16_t x)
{
return __ocml_exp_f16(x);
};
template <>
CK_TILE_DEVICE float exp<float>(float x)
{
return __ocml_exp_f32(x);
};
template <>
CK_TILE_DEVICE double exp<double>(double x)
{
return exp(x);
};
template <typename T>
CK_TILE_DEVICE T log(T x)
{
return type_convert<T>(__logf(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE fp16_t log<fp16_t>(fp16_t x)
{
return __ocml_log_f16(x);
};
template <>
CK_TILE_DEVICE float log<float>(float x)
{
return __logf(x);
};
template <>
CK_TILE_DEVICE double log<double>(double x)
{
return log(x);
};
template <typename T>
CK_TILE_DEVICE T pow(T x, T gamma)
{
return type_convert<T>(powf(type_convert<float>(x), type_convert<float>(gamma)));
};
template <>
CK_TILE_DEVICE float pow<float>(float x, float gamma)
{
return powf(x, gamma);
};
template <>
CK_TILE_DEVICE double pow<double>(double x, double gamma)
{
return pow(x, gamma);
};
template <typename T>
CK_TILE_DEVICE T expm1(T x)
{
return type_convert<T>(expm1f(type_convert<float>(x)));
};
template <>
CK_TILE_DEVICE float expm1<float>(float x)
{
return expm1f(x);
};
template <>
CK_TILE_DEVICE double expm1<double>(double x)
{
return expm1(x);
};
} // namespace ck_tile
......@@ -10,6 +10,7 @@
#include "ck_tile/core/numeric/half.hpp"
#include "ck_tile/core/numeric/bfloat16.hpp"
#include "ck_tile/core/numeric/float8.hpp"
#include "ck_tile/core/numeric/int8.hpp"
namespace ck_tile {
......@@ -60,6 +61,9 @@ CK_TILE_TYPE_CONVERT(bf16_t, bf16, float, float)
CK_TILE_TYPE_CONVERT(fp8_t, fp8, float, float)
CK_TILE_TYPE_CONVERT(bf8_t, bf8, float, float)
CK_TILE_TYPE_CONVERT(float, float, int8_t, int8)
CK_TILE_TYPE_CONVERT(int8_t, int8, float, float)
#undef CK_TILE_TYPE_CONVERT
#endif
......
......@@ -91,8 +91,10 @@ struct buffer_view<address_space_enum::generic,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE constexpr auto
get(index_t i, bool is_valid_element, bool_constant<oob_conditional_check> = {}) const
CK_TILE_DEVICE constexpr auto get(index_t i,
index_t linear_offset,
bool is_valid_element,
bool_constant<oob_conditional_check> = {}) const
{
// X contains multiple T
constexpr index_t scalar_per_t_vector = vector_traits<remove_cvref_t<T>>::vector_size;
......@@ -107,11 +109,11 @@ struct buffer_view<address_space_enum::generic,
#if CK_TILE_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS
X tmp;
__builtin_memcpy(&tmp, &(p_data_[i]), sizeof(X));
__builtin_memcpy(&tmp, &(p_data_[i + linear_offset]), sizeof(X));
return tmp;
#else
return *c_style_pointer_cast<const X*>(&p_data_[i]);
return *c_style_pointer_cast<const X*>(&p_data_[i + linear_offset]);
#endif
}
else
......@@ -134,17 +136,17 @@ struct buffer_view<address_space_enum::generic,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE void update(index_t i, bool is_valid_element, const X& x)
CK_TILE_DEVICE void update(index_t i, index_t linear_offset, bool is_valid_element, const X& x)
{
if constexpr(Op == memory_operation_enum::set)
{
this->template set<X>(i, is_valid_element, x);
this->template set<X>(i, linear_offset, is_valid_element, x);
}
// FIXME: remove memory_operation_enum::add
else if constexpr(Op == memory_operation_enum::add)
{
auto tmp = this->template get<X>(i, is_valid_element);
this->template set<X>(i, is_valid_element, x + tmp);
auto tmp = this->template get<X>(i, linear_offset, is_valid_element);
this->template set<X>(i, linear_offset, is_valid_element, x + tmp);
}
}
......@@ -154,7 +156,7 @@ struct buffer_view<address_space_enum::generic,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE void set(index_t i, bool is_valid_element, const X& x)
CK_TILE_DEVICE void set(index_t i, index_t linear_offset, bool is_valid_element, const X& x)
{
// X contains multiple T
constexpr index_t scalar_per_t_vector = vector_traits<remove_cvref_t<T>>::vector_size;
......@@ -169,9 +171,9 @@ struct buffer_view<address_space_enum::generic,
#if CK_TILE_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS
X tmp = x;
__builtin_memcpy(&(p_data_[i]), &tmp, sizeof(X));
__builtin_memcpy(&(p_data_[i + linear_offset]), &tmp, sizeof(X));
#else
*c_style_pointer_cast<X*>(&p_data_[i]) = x;
*c_style_pointer_cast<X*>(&p_data_[i + linear_offset]) = x;
#endif
}
}
......@@ -276,8 +278,10 @@ struct buffer_view<address_space_enum::global,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE constexpr auto
get(index_t i, bool is_valid_element, bool_constant<oob_conditional_check> = {}) const
CK_TILE_DEVICE constexpr auto get(index_t i,
index_t linear_offset,
bool is_valid_element,
bool_constant<oob_conditional_check> = {}) const
{
// X contains multiple T
constexpr index_t scalar_per_t_vector = vector_traits<remove_cvref_t<T>>::vector_size;
......@@ -303,7 +307,7 @@ struct buffer_view<address_space_enum::global,
t_per_x,
Coherence,
oob_conditional_check>(
p_data_, i, is_valid_element, buffer_size_);
p_data_, i + linear_offset, is_valid_element, buffer_size_);
}
else
{
......@@ -311,8 +315,11 @@ struct buffer_view<address_space_enum::global,
remove_cvref_t<T>,
t_per_x,
Coherence,
oob_conditional_check>(
p_data_, i, is_valid_element, buffer_size_, invalid_element_value_);
oob_conditional_check>(p_data_,
i + linear_offset,
is_valid_element,
buffer_size_,
invalid_element_value_);
}
}
else
......@@ -322,11 +329,11 @@ struct buffer_view<address_space_enum::global,
#if CK_TILE_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS
X tmp;
__builtin_memcpy(&tmp, &(p_data_[i]), sizeof(X));
__builtin_memcpy(&tmp, &(p_data_[i + linear_offset]), sizeof(X));
return tmp;
#else
return *c_style_pointer_cast<const X*>(&p_data_[i]);
return *c_style_pointer_cast<const X*>(&p_data_[i + linear_offset]);
#endif
}
else
......@@ -352,7 +359,8 @@ struct buffer_view<address_space_enum::global,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE constexpr auto get_raw(remove_cvref_t<X>& dst,
index_t i,
index_t v_offset,
index_t i_offset,
bool is_valid_element,
bool_constant<pre_nop> = {}) const
{
......@@ -366,7 +374,38 @@ struct buffer_view<address_space_enum::global,
constexpr index_t t_per_x = scalar_per_x_vector / scalar_per_t_vector;
amd_buffer_load_raw<remove_cvref_t<T>, t_per_x, Coherence, oob_conditional_check, pre_nop>(
dst, cached_buf_res_, i, is_valid_element, bool_constant<pre_nop>{});
dst, cached_buf_res_, v_offset, i_offset, is_valid_element, bool_constant<pre_nop>{});
}
// i is offset of T, not X. i should be aligned to X
template <typename X,
bool oob_conditional_check = true,
typename std::enable_if<
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE constexpr auto async_get(CK_TILE_LDS_ADDR remove_cvref_t<T>* smem,
index_t i,
index_t linear_offset,
bool is_valid_element,
bool_constant<oob_conditional_check> = {}) const
{
// X is vector of T
constexpr index_t scalar_per_t_vector = vector_traits<remove_cvref_t<T>>::vector_size;
constexpr index_t scalar_per_x_vector = vector_traits<remove_cvref_t<X>>::vector_size;
static_assert(scalar_per_x_vector % scalar_per_t_vector == 0,
"wrong! X should contain multiple T");
constexpr index_t t_per_x = scalar_per_x_vector / scalar_per_t_vector;
amd_async_buffer_load_with_oob<remove_cvref_t<T>, t_per_x, Coherence>(
smem,
cached_buf_res_,
i,
linear_offset,
is_valid_element,
bool_constant<oob_conditional_check>{});
}
// i is offset of T, not X. i should be aligned to X
......@@ -378,6 +417,7 @@ struct buffer_view<address_space_enum::global,
bool>::type = false>
CK_TILE_DEVICE constexpr auto async_get_raw(remove_cvref_t<T>* smem,
index_t i,
index_t linear_offset,
bool /*is_valid_element*/,
bool_constant<pre_nop> = {}) const
{
......@@ -391,7 +431,7 @@ struct buffer_view<address_space_enum::global,
constexpr index_t t_per_x = scalar_per_x_vector / scalar_per_t_vector;
amd_async_buffer_load_with_oob_raw<remove_cvref_t<T>, t_per_x, Coherence>(
smem, cached_buf_res_, i, bool_constant<pre_nop>{});
smem, cached_buf_res_, i, linear_offset, bool_constant<pre_nop>{});
}
// i is offset of T, not X. i should be aligned to X
......@@ -401,25 +441,25 @@ struct buffer_view<address_space_enum::global,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE void update(index_t i, bool is_valid_element, const X& x)
CK_TILE_DEVICE void update(index_t i, index_t linear_offset, bool is_valid_element, const X& x)
{
if constexpr(Op == memory_operation_enum::set)
{
this->template set<X>(i, is_valid_element, x);
this->template set<X>(i, linear_offset, is_valid_element, x);
}
else if constexpr(Op == memory_operation_enum::atomic_add)
{
this->template atomic_add<X>(i, is_valid_element, x);
this->template atomic_add<X>(i, linear_offset, is_valid_element, x);
}
else if constexpr(Op == memory_operation_enum::atomic_max)
{
this->template atomic_max<X>(i, is_valid_element, x);
this->template atomic_max<X>(i, linear_offset, is_valid_element, x);
}
// FIXME: remove memory_operation_enum::add
else if constexpr(Op == memory_operation_enum::add)
{
auto tmp = this->template get<X>(i, is_valid_element);
this->template set<X>(i, is_valid_element, x + tmp);
auto tmp = this->template get<X>(i, linear_offset, is_valid_element);
this->template set<X>(i, linear_offset, is_valid_element, x + tmp);
// tmp += x;
// this->template set<X>(i, is_valid_element, tmp);
}
......@@ -432,7 +472,7 @@ struct buffer_view<address_space_enum::global,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE void set(index_t i, bool is_valid_element, const X& x)
CK_TILE_DEVICE void set(index_t i, index_t linear_offset, bool is_valid_element, const X& x)
{
// X contains multiple T
constexpr index_t scalar_per_t_vector = vector_traits<remove_cvref_t<T>>::vector_size;
......@@ -453,7 +493,7 @@ struct buffer_view<address_space_enum::global,
constexpr index_t t_per_x = scalar_per_x_vector / scalar_per_t_vector;
amd_buffer_store<remove_cvref_t<T>, t_per_x, Coherence>(
x, p_data_, i, is_valid_element, buffer_size_);
x, p_data_, i + linear_offset, is_valid_element, buffer_size_);
}
else
{
......@@ -462,9 +502,9 @@ struct buffer_view<address_space_enum::global,
#if CK_TILE_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS
X tmp = x;
__builtin_memcpy(&(p_data_[i]), &tmp, sizeof(X));
__builtin_memcpy(&(p_data_[i + linear_offset]), &tmp, sizeof(X));
#else
*c_style_pointer_cast<X*>(&p_data_[i]) = x;
*c_style_pointer_cast<X*>(&p_data_[i + linear_offset]) = x;
#endif
}
}
......@@ -477,7 +517,7 @@ struct buffer_view<address_space_enum::global,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE void set_raw(index_t i, bool is_valid_element, const X& x)
CK_TILE_DEVICE void set_raw(index_t i, index_t linear_offset, bool is_valid_element, const X& x)
{
// X contains multiple T
constexpr index_t scalar_per_t_vector = vector_traits<remove_cvref_t<T>>::vector_size;
......@@ -489,7 +529,7 @@ struct buffer_view<address_space_enum::global,
constexpr index_t t_per_x = scalar_per_x_vector / scalar_per_t_vector;
amd_buffer_store_raw<remove_cvref_t<T>, t_per_x, Coherence, oob_conditional_check>(
x, p_data_, i, is_valid_element, buffer_size_);
x, p_data_, i, linear_offset, is_valid_element, buffer_size_);
}
template <typename X,
......@@ -497,7 +537,8 @@ struct buffer_view<address_space_enum::global,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE void atomic_add(index_t i, bool is_valid_element, const X& x)
CK_TILE_DEVICE void
atomic_add(index_t i, index_t linear_offset, bool is_valid_element, const X& x)
{
using scalar_t = typename vector_traits<remove_cvref_t<T>>::scalar_type;
......@@ -532,13 +573,13 @@ struct buffer_view<address_space_enum::global,
if constexpr(use_amd_buffer_addressing)
{
amd_buffer_atomic_add<remove_cvref_t<T>, t_per_x>(
x, p_data_, i, is_valid_element, buffer_size_);
x, p_data_, i + linear_offset, is_valid_element, buffer_size_);
}
else
{
if(is_valid_element)
{
atomic_add_g<remove_cvref_t<T>, t_per_x>(&p_data_[i], x);
atomic_add_g<remove_cvref_t<T>, t_per_x>(&p_data_[i + linear_offset], x);
}
}
}
......@@ -548,7 +589,8 @@ struct buffer_view<address_space_enum::global,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE void atomic_max(index_t i, bool is_valid_element, const X& x)
CK_TILE_DEVICE void
atomic_max(index_t i, index_t linear_offset, bool is_valid_element, const X& x)
{
// X contains multiple T
constexpr index_t scalar_per_t_vector = vector_traits<remove_cvref_t<T>>::vector_size;
......@@ -572,11 +614,11 @@ struct buffer_view<address_space_enum::global,
if constexpr(use_amd_buffer_addressing)
{
amd_buffer_atomic_max<remove_cvref_t<T>, t_per_x>(
x, p_data_, i, is_valid_element, buffer_size_);
x, p_data_, i + linear_offset, is_valid_element, buffer_size_);
}
else if(is_valid_element)
{
atomic_max_g<remove_cvref_t<T>, t_per_x>(&p_data_[i], x);
atomic_max_g<remove_cvref_t<T>, t_per_x>(&p_data_[i + linear_offset], x);
}
}
......@@ -668,8 +710,10 @@ struct buffer_view<address_space_enum::lds,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE constexpr auto
get(index_t i, bool is_valid_element, bool_constant<oob_conditional_check> = {}) const
CK_TILE_DEVICE constexpr auto get(index_t i,
index_t linear_offset,
bool is_valid_element,
bool_constant<oob_conditional_check> = {}) const
{
// X contains multiple T
constexpr index_t scalar_per_t_vector = vector_traits<remove_cvref_t<T>>::vector_size;
......@@ -684,14 +728,14 @@ struct buffer_view<address_space_enum::lds,
#if CK_TILE_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS
X tmp;
__builtin_memcpy(&tmp, &(p_data_[i]), sizeof(X));
__builtin_memcpy(&tmp, &(p_data_[i + linear_offset]), sizeof(X));
return tmp;
#else
using buf_t = ext_vector_t<typename vector_traits<remove_cvref_t<T>>::scalar_type,
scalar_per_t_vector * scalar_per_x_vector>;
// using buf_t = ushort __attribute__((ext_vector_type(8)));
auto rtn = *c_style_pointer_cast<const buf_t*>(&p_data_[i]);
auto rtn = *c_style_pointer_cast<const buf_t*>(&p_data_[i + linear_offset]);
return bit_cast<X>(rtn);
#endif
}
......@@ -708,6 +752,23 @@ struct buffer_view<address_space_enum::lds,
}
}
// i is offset of T, not X. i should be aligned to X
template <typename X,
bool oob_conditional_check = true,
bool pre_nop = false,
typename std::enable_if<
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE constexpr auto get_raw(remove_cvref_t<X>& dst,
index_t v_offset,
index_t i_offset,
bool /*is_valid_element*/,
bool_constant<pre_nop> = {}) const
{
smem_load<sizeof(X)>{}(dst, v_offset * sizeof(T), i_offset * sizeof(T));
}
// i is offset of T, not X. i should be aligned to X
template <memory_operation_enum Op,
typename X,
......@@ -715,17 +776,17 @@ struct buffer_view<address_space_enum::lds,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE void update(index_t i, bool is_valid_element, const X& x)
CK_TILE_DEVICE void update(index_t i, index_t linear_offset, bool is_valid_element, const X& x)
{
if constexpr(Op == memory_operation_enum::set)
{
this->template set<X>(i, is_valid_element, x);
this->template set<X>(i, linear_offset, is_valid_element, x);
}
// FIXME: remove memory_operation_enum::add
else if constexpr(Op == memory_operation_enum::add)
{
auto tmp = this->template get<X>(i, is_valid_element);
this->template set<X>(i, is_valid_element, x + tmp);
auto tmp = this->template get<X>(i, linear_offset, is_valid_element);
this->template set<X>(i, linear_offset, is_valid_element, x + tmp);
}
}
......@@ -735,7 +796,7 @@ struct buffer_view<address_space_enum::lds,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE void set(index_t i, bool is_valid_element, const X& x)
CK_TILE_DEVICE void set(index_t i, index_t linear_offset, bool is_valid_element, const X& x)
{
// X contains multiple T
constexpr index_t scalar_per_t_vector = vector_traits<remove_cvref_t<T>>::vector_size;
......@@ -751,6 +812,7 @@ struct buffer_view<address_space_enum::lds,
bool constexpr workaround_int8_ds_write_issue = false;
#endif
i += linear_offset; // simplicity
if constexpr(std::is_same<typename vector_traits<remove_cvref_t<T>>::scalar_type,
int8_t>::value &&
workaround_int8_ds_write_issue)
......@@ -952,8 +1014,10 @@ struct buffer_view<address_space_enum::vgpr,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE constexpr auto
get(index_t i, bool is_valid_element, bool_constant<oob_conditional_check> = {}) const
CK_TILE_DEVICE constexpr auto get(index_t i,
index_t /*linear_offset*/,
bool is_valid_element,
bool_constant<oob_conditional_check> = {}) const
{
// X contains multiple T
constexpr index_t scalar_per_t_vector = vector_traits<remove_cvref_t<T>>::vector_size;
......@@ -995,17 +1059,17 @@ struct buffer_view<address_space_enum::vgpr,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE void update(index_t i, bool is_valid_element, const X& x)
CK_TILE_DEVICE void update(index_t i, index_t linear_offset, bool is_valid_element, const X& x)
{
if constexpr(Op == memory_operation_enum::set)
{
this->template set<X>(i, is_valid_element, x);
this->template set<X>(i, linear_offset, is_valid_element, x);
}
// FIXME: remove memory_operation_enum::add
else if constexpr(Op == memory_operation_enum::add)
{
auto tmp = this->template get<X>(i, is_valid_element);
this->template set<X>(i, is_valid_element, x + tmp);
auto tmp = this->template get<X>(i, linear_offset, is_valid_element);
this->template set<X>(i, linear_offset, is_valid_element, x + tmp);
}
}
......@@ -1015,7 +1079,7 @@ struct buffer_view<address_space_enum::vgpr,
std::is_same<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<T>>::scalar_type>::value,
bool>::type = false>
CK_TILE_DEVICE void set(index_t i, bool is_valid_element, const X& x)
CK_TILE_DEVICE void set(index_t i, index_t linear_offset, bool is_valid_element, const X& x)
{
// X contains multiple T
constexpr index_t scalar_per_t_vector = vector_traits<remove_cvref_t<T>>::vector_size;
......@@ -1030,9 +1094,9 @@ struct buffer_view<address_space_enum::vgpr,
#if CK_TILE_EXPERIMENTAL_USE_MEMCPY_FOR_VECTOR_ACCESS
X tmp = x;
__builtin_memcpy(&(p_data_[i]), &tmp, sizeof(X));
__builtin_memcpy(&(p_data_[i + linear_offset]), &tmp, sizeof(X));
#else
*c_style_pointer_cast<X*>(&p_data_[i]) = x;
*c_style_pointer_cast<X*>(&p_data_[i + linear_offset]) = x;
#endif
}
}
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -12,6 +12,7 @@
#include "ck_tile/core/tensor/tile_window.hpp"
#include "ck_tile/core/utility/type_traits.hpp"
#include "ck_tile/core/tensor/tile_window.hpp"
#include "ck_tile/core/tensor/tile_window_linear.hpp"
#include "ck_tile/core/tensor/null_tile_window.hpp"
#include "ck_tile/core/tensor/null_tensor.hpp"
......@@ -28,9 +29,48 @@ CK_TILE_DEVICE auto load_tile(const tile_window_with_static_distribution<BottomT
NumCoord>& tile_window,
bool_constant<oob_conditional_check> = {})
{
return tile_window.load(bool_constant<oob_conditional_check>{});
return tile_window.load(number<-1>{}, bool_constant<oob_conditional_check>{});
}
template <typename BottomTensorView_,
typename WindowLengths_,
typename TileDistribution_,
typename LinearBottomDims_,
bool oob_conditional_check = true>
CK_TILE_DEVICE auto load_tile(const tile_window_linear<BottomTensorView_,
WindowLengths_,
TileDistribution_,
LinearBottomDims_>& tile_window,
bool_constant<oob_conditional_check> = {})
{
return tile_window.load(number<-1>{}, bool_constant<oob_conditional_check>{});
}
template <typename DistributedTensor_,
typename BottomTensorView_,
typename WindowLengths_,
typename TileDistribution_,
index_t NumCoord,
bool oob_conditional_check = true>
CK_TILE_DEVICE auto load_tile(DistributedTensor_& dst_tile,
const tile_window_with_static_distribution<BottomTensorView_,
WindowLengths_,
TileDistribution_,
NumCoord>& tile_window,
bool_constant<oob_conditional_check> = {})
{
return tile_window.load(dst_tile, bool_constant<oob_conditional_check>{});
}
/**
* @brief Loads a tile of data using inline assembly.
*
* @note Bare in mind that loading data this way, you have to manually initialize your
* thread buffer and synchronize load afterwards in order to make sure it's done before
* using loaded data from registers
* @see `tile_window_with_static_distribution::init_raw()` and `buffer_view.hpp`
* @see `buffer_load_fence()`
*/
template <typename T,
typename BottomTensorView_,
typename WindowLengths_,
......@@ -46,7 +86,27 @@ CK_TILE_DEVICE auto load_tile_raw(T& tile,
bool_constant<oob_conditional_check> = {},
bool_constant<pre_nop> = {})
{
tile_window.load_raw(tile, bool_constant<oob_conditional_check>{}, bool_constant<pre_nop>{});
tile_window.load_raw(
tile, number<-1>{}, bool_constant<oob_conditional_check>{}, bool_constant<pre_nop>{});
}
template <typename T,
typename BottomTensorView_,
typename WindowLengths_,
typename TileDistribution_,
typename LinearBottomDims_,
bool oob_conditional_check = true,
bool pre_nop = false>
CK_TILE_DEVICE auto load_tile_raw(T& tile,
const tile_window_linear<BottomTensorView_,
WindowLengths_,
TileDistribution_,
LinearBottomDims_>& tile_window,
bool_constant<oob_conditional_check> = {},
bool_constant<pre_nop> = {})
{
tile_window.load_raw(
tile, number<-1>{}, bool_constant<oob_conditional_check>{}, bool_constant<pre_nop>{});
}
template <typename LdsTileWindow_,
......@@ -66,7 +126,26 @@ async_load_tile_raw(LdsTileWindow_&& lds_tile,
bool_constant<pre_nop> = {})
{
return tile_window.async_load_raw(
lds_tile, bool_constant<oob_conditional_check>{}, bool_constant<pre_nop>{});
lds_tile, number<-1>{}, bool_constant<oob_conditional_check>{}, bool_constant<pre_nop>{});
}
template <typename LdsTileWindow_,
typename BottomTensorView_,
typename WindowLengths_,
typename TileDistribution_,
typename LinearBottomDims_,
bool oob_conditional_check = true,
bool pre_nop = false>
CK_TILE_DEVICE auto async_load_tile_raw(LdsTileWindow_&& lds_tile,
const tile_window_linear<BottomTensorView_,
WindowLengths_,
TileDistribution_,
LinearBottomDims_>& tile_window,
bool_constant<oob_conditional_check> = {},
bool_constant<pre_nop> = {})
{
return tile_window.async_load_raw(
lds_tile, number<-1>{}, bool_constant<oob_conditional_check>{}, bool_constant<pre_nop>{});
}
CK_TILE_DEVICE auto async_load_fence(index_t cnt = 0)
......
......@@ -80,6 +80,13 @@ CK_TILE_DEVICE constexpr auto make_tile_window(null_tensor_view,
return null_tile_window<remove_cvref_t<WindowLengths>>{window_lengths};
}
template <typename WindowLengths, typename StaticTileDistribution>
CK_TILE_DEVICE constexpr auto make_tile_window(const null_tile_window<WindowLengths>& t,
const StaticTileDistribution&)
{
return t;
}
template <typename WindowLengths>
CK_TILE_DEVICE void
move_tile_window(null_tile_window<WindowLengths>&,
......
......@@ -109,7 +109,7 @@ CK_TILE_DEVICE void shuffle_tile_impl_in_thread(OutTensor& out_tensor, const InT
// get input vectors
static_for<0, num_vec_in, 1>{}([&](auto i) {
constexpr auto idx_y_in = generate_array(
constexpr auto idx_y_in = generate_tuple(
[&](auto ii) {
return ii == y_dim_vec_out ? idx_y_start[ii] + i : idx_y_start[ii];
},
......
......@@ -10,6 +10,7 @@
#include "ck_tile/core/container/container_helper.hpp"
#include "ck_tile/core/numeric/math.hpp"
#include "ck_tile/core/tensor/tile_window.hpp"
#include "ck_tile/core/tensor/tile_window_linear.hpp"
#include "ck_tile/core/utility/type_traits.hpp"
namespace ck_tile {
......@@ -72,7 +73,7 @@ store_tile(tile_window_with_static_distribution<BottomTensorView_,
NumCoord>& tile_window,
const static_distributed_tensor<DataType_, TileDistribution_>& dstr_tensor)
{
tile_window.store(dstr_tensor);
tile_window.store(dstr_tensor, number<-1>{});
}
template <typename BottomTensorView_,
......@@ -87,7 +88,33 @@ store_tile_raw(tile_window_with_static_distribution<BottomTensorView_,
NumCoord>& tile_window,
const static_distributed_tensor<DataType_, TileDistribution_>& dstr_tensor)
{
tile_window.store_raw(dstr_tensor);
tile_window.store_raw(dstr_tensor, number<-1>{});
}
template <typename BottomTensorView_,
typename WindowLengths_,
typename TileDistribution_,
typename LinearBottomDims_,
typename DataType_>
CK_TILE_DEVICE void store_tile(
tile_window_linear<BottomTensorView_, WindowLengths_, TileDistribution_, LinearBottomDims_>&
tile_window,
const static_distributed_tensor<DataType_, TileDistribution_>& dstr_tensor)
{
tile_window.store(dstr_tensor, number<-1>{});
}
template <typename BottomTensorView_,
typename WindowLengths_,
typename TileDistribution_,
typename LinearBottomDims_,
typename DataType_>
CK_TILE_DEVICE void store_tile_raw(
tile_window_linear<BottomTensorView_, WindowLengths_, TileDistribution_, LinearBottomDims_>&
tile_window,
const static_distributed_tensor<DataType_, TileDistribution_>& dstr_tensor)
{
tile_window.store_raw(dstr_tensor, number<-1>{});
}
} // namespace ck_tile
......@@ -16,6 +16,24 @@
namespace ck_tile {
/*
* tensor_view
* abstract the underneath memory buffer(global, LDS, etc...)
* and provide a unified get/set function for access
*
* For addressing into the buffer we use 2 variable to control:
* coord : ND tensor coordinate, will calculate the actual offset inside
* linear_offset : 1D offset, will be used in the immediate field of
* the buffer instruction to help reduce register usage
*
* User can use either of the field, or both to indexing into the tensor
*
* We usually provide 2 set of API for buffer get/set, e.g.
* get_vectorized_elements()/get_vectorized_elements_raw()
* the former usually will call intrinsic or normal C function, the later
* usually will call inline-asm function
*
*/
template <typename BufferView_,
typename TensorDesc_,
memory_operation_enum DstInMemOp_ = memory_operation_enum::set>
......@@ -49,22 +67,6 @@ struct tensor_view
CK_TILE_HOST_DEVICE constexpr auto& get_buffer_view() { return buf_; }
#if 0
CK_TILE_HOST_DEVICE constexpr DataType get_element(const TensorCoord& coord) const
{
return buf_.template get<DataType>(
coord.get_offset(),
coordinate_has_valid_offset_assuming_top_index_is_valid(desc_, coord));
}
CK_TILE_HOST_DEVICE constexpr void set_element(const TensorCoord& coord, const DataType& x)
{
buf_.template set<DataType>(
coord.get_offset(),
coordinate_has_valid_offset_assuming_top_index_is_valid(desc_, coord),
x);
}
#endif
// X is vector of DataType.
// "coord" is coordinate of DataType, not X. "coord" should be aligned to X
template <typename X,
......@@ -75,14 +77,34 @@ struct tensor_view
bool>::type = false>
CK_TILE_HOST_DEVICE constexpr remove_cvref_t<X>
get_vectorized_elements(const TensorCoord& coord,
index_t linear_offset,
bool_constant<oob_conditional_check> = {}) const
{
return buf_.template get<X>(
coord.get_offset(),
linear_offset,
coordinate_has_valid_offset_assuming_top_index_is_valid(desc_, coord),
bool_constant<oob_conditional_check>{});
}
template <typename X,
bool oob_conditional_check = true,
typename std::enable_if<
std::is_same_v<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<DataType>>::scalar_type>,
bool>::type = false>
CK_TILE_HOST_DEVICE constexpr remove_cvref_t<X>
get_vectorized_elements(const TensorCoord& coord,
index_t linear_offset,
bool is_valid_element, // flag
bool_constant<oob_conditional_check> = {}) const
{
return buf_.template get<X>(coord.get_offset(),
linear_offset,
is_valid_element,
bool_constant<oob_conditional_check>{});
}
// X is vector of DataType.
// "coord" is coordinate of DataType, not X. "coord" should be aligned to X
template <typename X,
......@@ -94,12 +116,90 @@ struct tensor_view
bool>::type = false>
CK_TILE_HOST_DEVICE void get_vectorized_elements_raw(remove_cvref_t<X>& dst,
const TensorCoord& coord,
index_t linear_offset,
bool_constant<oob_conditional_check> = {},
bool_constant<pre_nop> = {}) const
{
return buf_.template get_raw<X, oob_conditional_check, pre_nop>(
dst,
coord.get_offset(),
linear_offset,
coordinate_has_valid_offset_assuming_top_index_is_valid(desc_, coord),
bool_constant<pre_nop>{});
}
template <typename X,
bool oob_conditional_check = true,
bool pre_nop = false,
typename std::enable_if<
std::is_same_v<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<DataType>>::scalar_type>,
bool>::type = false>
CK_TILE_HOST_DEVICE void get_vectorized_elements_raw(remove_cvref_t<X>& dst,
const TensorCoord& coord,
index_t linear_offset,
bool is_valid_element,
bool_constant<oob_conditional_check> = {},
bool_constant<pre_nop> = {}) const
{
return buf_.template get_raw<X, oob_conditional_check, pre_nop>(
dst, coord.get_offset(), linear_offset, is_valid_element, bool_constant<pre_nop>{});
}
template <typename X,
bool oob_conditional_check = true,
typename std::enable_if<
std::is_same_v<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<DataType>>::scalar_type>,
bool>::type = false>
CK_TILE_HOST_DEVICE constexpr void
async_get_vectorized_elements(CK_TILE_LDS_ADDR remove_cvref_t<DataType>* smem,
const TensorCoord& coord,
index_t linear_offset) const
{
return buf_.template async_get<X>(
smem,
coord.get_offset(),
linear_offset,
coordinate_has_valid_offset_assuming_top_index_is_valid(desc_, coord),
bool_constant<oob_conditional_check>{});
}
template <typename X,
bool oob_conditional_check = true,
typename std::enable_if<
std::is_same_v<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<DataType>>::scalar_type>,
bool>::type = false>
CK_TILE_HOST_DEVICE constexpr void
async_get_vectorized_elements(CK_TILE_LDS_ADDR remove_cvref_t<DataType>* smem,
const TensorCoord& coord,
index_t linear_offset,
bool is_valid_element) const
{
return buf_.template async_get<X>(smem,
coord.get_offset(),
linear_offset,
is_valid_element,
bool_constant<oob_conditional_check>{});
}
template <typename X,
bool pre_nop = false,
typename std::enable_if<
std::is_same_v<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<DataType>>::scalar_type>,
bool>::type = false>
CK_TILE_HOST_DEVICE constexpr void
async_get_vectorized_elements_raw(remove_cvref_t<DataType>* smem,
const TensorCoord& coord,
index_t linear_offset,
bool_constant<pre_nop> = {}) const
{
return buf_.template async_get_raw<X>(
smem,
coord.get_offset(),
linear_offset,
coordinate_has_valid_offset_assuming_top_index_is_valid(desc_, coord),
bool_constant<pre_nop>{});
}
......@@ -110,11 +210,15 @@ struct tensor_view
std::is_same_v<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<DataType>>::scalar_type>,
bool>::type = false>
CK_TILE_HOST_DEVICE constexpr void async_get_vectorized_elements_raw(
remove_cvref_t<DataType>* smem, const TensorCoord& coord, bool_constant<pre_nop> = {}) const
CK_TILE_HOST_DEVICE constexpr void
async_get_vectorized_elements_raw(remove_cvref_t<DataType>* smem,
const TensorCoord& coord,
index_t linear_offset,
bool is_valid_element,
bool_constant<pre_nop> = {}) const
{
return buf_.template async_get_raw<X>(
smem, coord.get_offset(), true /*not used*/, bool_constant<pre_nop>{});
smem, coord.get_offset(), linear_offset, is_valid_element, bool_constant<pre_nop>{});
}
// X is vector of DataType.
......@@ -125,11 +229,15 @@ struct tensor_view
std::is_same_v<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<DataType>>::scalar_type>,
bool>::type = false>
CK_TILE_HOST_DEVICE constexpr void set_vectorized_elements(
const TensorCoord& coord, const X& x, bool_constant<oob_conditional_check> = {})
CK_TILE_HOST_DEVICE constexpr void
set_vectorized_elements(const TensorCoord& coord,
index_t linear_offset,
const X& x,
bool_constant<oob_conditional_check> = {})
{
buf_.template set<X, oob_conditional_check>(
coord.get_offset(),
linear_offset,
coordinate_has_valid_offset_assuming_top_index_is_valid(desc_, coord),
x);
}
......@@ -140,15 +248,53 @@ struct tensor_view
std::is_same_v<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<DataType>>::scalar_type>,
bool>::type = false>
CK_TILE_HOST_DEVICE constexpr void set_vectorized_elements_raw(
const TensorCoord& coord, const X& x, bool_constant<oob_conditional_check> = {})
CK_TILE_HOST_DEVICE constexpr void
set_vectorized_elements(const TensorCoord& coord,
index_t linear_offset,
bool is_valid_element,
const X& x,
bool_constant<oob_conditional_check> = {})
{
buf_.template set<X, oob_conditional_check>(
coord.get_offset(), linear_offset, is_valid_element, x);
}
template <typename X,
bool oob_conditional_check = true,
typename std::enable_if<
std::is_same_v<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<DataType>>::scalar_type>,
bool>::type = false>
CK_TILE_HOST_DEVICE constexpr void
set_vectorized_elements_raw(const TensorCoord& coord,
index_t linear_offset,
const X& x,
bool_constant<oob_conditional_check> = {})
{
buf_.template set_raw<X, oob_conditional_check>(
coord.get_offset(),
linear_offset,
coordinate_has_valid_offset_assuming_top_index_is_valid(desc_, coord),
x);
}
template <typename X,
bool oob_conditional_check = true,
typename std::enable_if<
std::is_same_v<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<DataType>>::scalar_type>,
bool>::type = false>
CK_TILE_HOST_DEVICE constexpr void
set_vectorized_elements_raw(const TensorCoord& coord,
index_t linear_offset,
bool is_valid_element,
const X& x,
bool_constant<oob_conditional_check> = {})
{
buf_.template set_raw<X, oob_conditional_check>(
coord.get_offset(), linear_offset, is_valid_element, x);
}
// X is vector of DataType.
// "coord" is coordinate of DataType, not X. "coord" should be aligned to X
template <typename X,
......@@ -157,15 +303,36 @@ struct tensor_view
std::is_same_v<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<DataType>>::scalar_type>,
bool>::type = false>
CK_TILE_HOST_DEVICE constexpr void update_vectorized_elements(
const TensorCoord& coord, const X& x, bool_constant<oob_conditional_check> = {})
CK_TILE_HOST_DEVICE constexpr void
update_vectorized_elements(const TensorCoord& coord,
index_t linear_offset,
const X& x,
bool_constant<oob_conditional_check> = {})
{
buf_.template update<DstInMemOp, X, oob_conditional_check>(
coord.get_offset(),
linear_offset,
coordinate_has_valid_offset_assuming_top_index_is_valid(desc_, coord),
x);
}
template <typename X,
bool oob_conditional_check = true,
typename std::enable_if<
std::is_same_v<typename vector_traits<remove_cvref_t<X>>::scalar_type,
typename vector_traits<remove_cvref_t<DataType>>::scalar_type>,
bool>::type = false>
CK_TILE_HOST_DEVICE constexpr void
update_vectorized_elements(const TensorCoord& coord,
index_t linear_offset,
bool is_valid_element,
const X& x,
bool_constant<oob_conditional_check> = {})
{
buf_.template update<DstInMemOp, X, oob_conditional_check>(
coord.get_offset(), linear_offset, is_valid_element, x);
}
CK_TILE_HOST_DEVICE void print() const
{
printf("tensor_view{");
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
......@@ -18,6 +18,8 @@
namespace ck_tile {
// Note: this tile window do not support single issue
// you need to use tile_window_linear structure for this purpose
template <typename BottomTensorView_,
typename WindowLengths_,
typename StaticTileDistribution_,
......@@ -41,6 +43,7 @@ struct tile_window_with_static_distribution
static constexpr auto I0 = number<0>{};
static constexpr auto I1 = number<1>{};
static_assert(NumCoord == 1);
// TODO: check WindowLengths and StaticTileDistribution are consistent
......@@ -189,7 +192,8 @@ struct tile_window_with_static_distribution
constexpr auto idx_diff_ys =
SFC_Ys::get_step_between(number<0>{}, number<iCoord * NumAccessPerCoord>{});
constexpr auto idx_diff_ps_ys = container_concat(array<index_t, NDimP>{0}, idx_diff_ys);
constexpr auto idx_diff_ps_ys = container_concat(
generate_tuple([&](auto) { return number<0>{}; }, number<NDimP>{}), idx_diff_ys);
move_window_adaptor_and_bottom_tensor_thread_coordinate(
window_adaptor_thread_coord, bottom_tensor_thread_coord, idx_diff_ps_ys);
......@@ -222,10 +226,11 @@ struct tile_window_with_static_distribution
// move thread's window adaptor coordinate and bottom tensor coordinate
// [p0, p1, ..., y0, y1, ...] ==> [x0, x1, ...] ==> [x0', x1', ...] ==> [offset]
template <typename ATopIndex>
CK_TILE_DEVICE void move_window_adaptor_and_bottom_tensor_thread_coordinate(
WindowAdaptorCoord& window_adaptor_thread_coord,
BottomTensorCoord& bottom_tensor_thread_coord,
const AdaptorTopIndex& idx_diff_adaptor_top) const
const ATopIndex& idx_diff_adaptor_top) const
{
array<index_t, NDimBottomTensor> idx_diff_adaptor_bottom;
......@@ -279,20 +284,28 @@ struct tile_window_with_static_distribution
get_container_subset(window_adaptor_ps_ys_vector_strides, y_dims));
}
CK_TILE_DEVICE constexpr auto get_num_access() const { return load_store_traits::NumAccess; }
CK_TILE_DEVICE constexpr auto get_num_of_access() const { return load_store_traits::NumAccess; }
template <bool oob_conditional_check = true>
CK_TILE_DEVICE auto load(bool_constant<oob_conditional_check> = {}) const
template <index_t i_access_unsupport_ = -1, bool oob_conditional_check = true>
CK_TILE_DEVICE auto load(number<i_access_unsupport_> = {},
bool_constant<oob_conditional_check> = {}) const
{
using Traits = load_store_traits;
constexpr auto tile_dstr = TileDstr{};
auto dst_tensor = make_static_distributed_tensor<DataType>(tile_dstr);
load(dst_tensor, bool_constant<oob_conditional_check>{});
return dst_tensor;
}
template <typename DistributedTensor, bool oob_conditional_check = true>
CK_TILE_DEVICE auto load(DistributedTensor& dst_tensor,
bool_constant<oob_conditional_check> = {}) const
{
using Traits = load_store_traits;
using vector_t = typename Traits::vector_t;
using SFC_Ys = typename Traits::SFC_Ys;
constexpr auto tile_dstr = TileDstr{};
auto dst_tensor = make_static_distributed_tensor<DataType>(tile_dstr);
// loop over thread tensor space [y0, y1, ...]
static_for<0, NumCoord, 1>{}([&](auto iCoord) {
/// TODO: use structure binding (to be captured later) if compiled in C++20
......@@ -308,11 +321,11 @@ struct tile_window_with_static_distribution
// read from bottom tensor
const vector_t vec_value =
get_bottom_tensor_view().template get_vectorized_elements<vector_t>(
bottom_tensor_thread_coord, bool_constant<oob_conditional_check>{});
bottom_tensor_thread_coord, 0, bool_constant<oob_conditional_check>{});
#if 1
// write into distributed tensor
static_for<0, Traits::ScalarPerVector, 1>{}([&](auto j) {
constexpr auto idx_ys = generate_array(
constexpr auto idx_ys = generate_tuple(
[&](auto jj) {
return jj == Traits::VectorDimY ? (idx_ys_start[jj] + j)
: idx_ys_start[jj];
......@@ -338,20 +351,23 @@ struct tile_window_with_static_distribution
{
constexpr auto idx_diff_ys = SFC_Ys::get_forward_step(iAccess);
constexpr auto idx_diff_ps_ys =
container_concat(array<index_t, NDimP>{0}, idx_diff_ys);
constexpr auto idx_diff_ps_ys = container_concat(
generate_tuple([&](auto) { return number<0>{}; }, number<NDimP>{}),
idx_diff_ys);
move_window_adaptor_and_bottom_tensor_thread_coordinate(
window_adaptor_thread_coord, bottom_tensor_thread_coord, idx_diff_ps_ys);
}
});
});
return dst_tensor;
}
template <typename DstTile, bool oob_conditional_check = true, bool pre_nop = false>
template <typename DstTile,
index_t i_access_unsupport_ = -1,
bool oob_conditional_check = true,
bool pre_nop = false>
CK_TILE_DEVICE void load_raw(DstTile& dst_tensor,
number<i_access_unsupport_> = {},
bool_constant<oob_conditional_check> = {},
bool_constant<pre_nop> = {}) const
{
......@@ -397,6 +413,7 @@ struct tile_window_with_static_distribution
get_bottom_tensor_view().template get_vectorized_elements_raw<vector_t>(
dst_vec_tbuf.template at<d / Traits::ScalarPerVector>(),
bottom_tensor_thread_coord,
0 /**/,
bool_constant<oob_conditional_check>{},
pre_nop_);
#if CK_TILE_WORKAROUND_ROCM_6_1_SCRATCH_MEMORY_ISSUE || \
......@@ -409,23 +426,24 @@ struct tile_window_with_static_distribution
{
constexpr auto idx_diff_ys = SFC_Ys::get_forward_step(iAccess);
constexpr auto idx_diff_ps_ys =
container_concat(array<index_t, NDimP>{0}, idx_diff_ys);
constexpr auto idx_diff_ps_ys = container_concat(
generate_tuple([&](auto) { return number<0>{}; }, number<NDimP>{}),
idx_diff_ys);
move_window_adaptor_and_bottom_tensor_thread_coordinate(
window_adaptor_thread_coord, bottom_tensor_thread_coord, idx_diff_ps_ys);
}
});
});
#if CK_TILE_WORKAROUND_ROCM_6_1_SCRATCH_MEMORY_ISSUE
asm volatile("; this inline asm is workaround to prevent compiler from using too much "
"scratch memory" ::);
#endif
}
// TODO: currently async load only implemented in inline asm
template <typename LdsTileWindow_, bool oob_conditional_check = true, bool pre_nop = false>
template <typename LdsTileWindow_,
index_t i_access_unsupport_ = -1,
bool oob_conditional_check = true,
bool pre_nop = false>
CK_TILE_DEVICE auto async_load_raw(LdsTileWindow_&& lds_tile,
number<i_access_unsupport_> = {},
bool_constant<oob_conditional_check> = {},
bool_constant<pre_nop> = {}) const
{
......@@ -467,7 +485,7 @@ struct tile_window_with_static_distribution
// loop over thread tensor space [y0, y1, ...]
static_for<0, NumCoord, 1>{}([&](auto iCoord) {
// TODO: use structure binding (to be captured later) if compiled in C++20
/// TODO: use structure binding (to be captured later) if compiled in C++20
auto window_adaptor_thread_coord = pre_computed_coords_[iCoord][I0];
auto bottom_tensor_thread_coord = pre_computed_coords_[iCoord][I1];
......@@ -482,15 +500,16 @@ struct tile_window_with_static_distribution
// read from bottom tensor
get_bottom_tensor_view().template async_get_vectorized_elements_raw<vector_t>(
smem, bottom_tensor_thread_coord, pre_nop_);
smem, bottom_tensor_thread_coord, 0, pre_nop_);
// move thread coordinate
if constexpr(iCoordAccess != (NumAccessPerCoord - 1))
{
constexpr auto idx_diff_ys = SFC_Ys::get_forward_step(iAccess);
constexpr auto idx_diff_ps_ys =
container_concat(array<index_t, NDimP>{0}, idx_diff_ys);
constexpr auto idx_diff_ps_ys = container_concat(
generate_tuple([&](auto) { return number<0>{}; }, number<NDimP>{}),
idx_diff_ys);
move_window_adaptor_and_bottom_tensor_thread_coordinate(
window_adaptor_thread_coord, bottom_tensor_thread_coord, idx_diff_ps_ys);
......@@ -501,8 +520,81 @@ struct tile_window_with_static_distribution
});
}
template <bool oob_conditional_check = true>
template <typename LdsTileWindow_,
index_t i_access_unsupport_ = -1,
bool oob_conditional_check = true>
CK_TILE_DEVICE auto async_load(LdsTileWindow_&& lds_tile,
number<i_access_unsupport_> = {},
bool_constant<oob_conditional_check> = {}) const
{
using LdsTileWindow = remove_cvref_t<LdsTileWindow_>;
using LdsDataType = typename LdsTileWindow::DataType;
// issues * warps * lanes
static_assert(LdsTileWindow::get_num_of_dimension() == 3); // TODO: hard coded
// TODO: LDS offset is not good for intrinsic based implementation(compiler can't figure out
// dependency) hence avoid use offset based solution. size_per_buf should be zero (how to
// check?)
constexpr index_t size_per_buf =
lds_tile.get_bottom_tensor_view().get_tensor_descriptor().calculate_offset(
make_tuple(number<0>{}, number<0>{}, number<0>{}));
constexpr index_t size_per_wave =
lds_tile.get_bottom_tensor_view().get_tensor_descriptor().calculate_offset(
make_tuple(number<0>{}, number<1>{}, number<0>{})) -
size_per_buf;
constexpr index_t size_per_issue =
lds_tile.get_bottom_tensor_view().get_tensor_descriptor().calculate_offset(
make_tuple(number<1>{}, number<0>{}, number<0>{})) -
size_per_buf;
const index_t m0_init_value = size_per_buf + size_per_wave * get_warp_id();
using Traits = load_store_traits;
using vector_t = typename Traits::vector_t;
using SFC_Ys = typename Traits::SFC_Ys;
// TODO: we force CK_TILE_LDS_ADDR
CK_TILE_LDS_ADDR LdsDataType* smem =
lds_tile.get_bottom_tensor_view().get_buffer_view().p_data_ + m0_init_value;
// loop over thread tensor space [y0, y1, ...]
static_for<0, NumCoord, 1>{}([&](auto iCoord) {
/// TODO: use structure binding (to be captured later) if compiled in C++20
auto window_adaptor_thread_coord = pre_computed_coords_[iCoord][I0];
auto bottom_tensor_thread_coord = pre_computed_coords_[iCoord][I1];
static_for<0, NumAccessPerCoord, 1>{}([&](auto iCoordAccess) {
constexpr auto iAccess = number<iCoord * NumAccessPerCoord + iCoordAccess>{};
// read from bottom tensor
get_bottom_tensor_view().template async_get_vectorized_elements<vector_t>(
smem, bottom_tensor_thread_coord, 0, bool_constant<oob_conditional_check>{});
// move thread coordinate
if constexpr(iCoordAccess != (NumAccessPerCoord - 1))
{
constexpr auto idx_diff_ys = SFC_Ys::get_forward_step(iAccess);
constexpr auto idx_diff_ps_ys = container_concat(
generate_tuple([&](auto) { return number<0>{}; }, number<NDimP>{}),
idx_diff_ys);
move_window_adaptor_and_bottom_tensor_thread_coordinate(
window_adaptor_thread_coord, bottom_tensor_thread_coord, idx_diff_ps_ys);
smem += size_per_issue; // Note we manually increase the per-issue offset
}
});
});
}
template <index_t i_access_unsupport_ = -1, bool oob_conditional_check = true>
CK_TILE_DEVICE void store(const static_distributed_tensor<DataType, TileDstr>& dstr_tensor,
number<i_access_unsupport_> = {},
bool_constant<oob_conditional_check> = {}) const
{
using Traits = load_store_traits;
......@@ -515,7 +607,6 @@ struct tile_window_with_static_distribution
// loop over thread tensor space [y0, y1, ...]
static_for<0, NumCoord, 1>{}([&](auto iCoord) {
/// TODO: use structure binding (to be captured later) if compiled in C++20
auto window_adaptor_thread_coord = pre_computed_coords_[iCoord][I0];
auto bottom_tensor_thread_coord = pre_computed_coords_[iCoord][I1];
......@@ -530,7 +621,7 @@ struct tile_window_with_static_distribution
vector_t vec_value;
static_for<0, Traits::ScalarPerVector, 1>{}([&](auto j) {
constexpr auto idx_ys = generate_array(
constexpr auto idx_ys = generate_tuple(
[&](auto jj) {
return jj == Traits::VectorDimY ? (idx_ys_start[jj] + j)
: idx_ys_start[jj];
......@@ -548,15 +639,19 @@ struct tile_window_with_static_distribution
// write into bottom tensor
get_bottom_tensor_view().template set_vectorized_elements<vector_t>(
bottom_tensor_thread_coord, vec_value, bool_constant<oob_conditional_check>{});
bottom_tensor_thread_coord,
0,
vec_value,
bool_constant<oob_conditional_check>{});
// move thread coordinate
if constexpr(iCoordAccess != (NumAccessPerCoord - 1))
{
constexpr auto idx_diff_ys = SFC_Ys::get_forward_step(iAccess);
constexpr auto idx_diff_ps_ys =
container_concat(array<index_t, NDimP>{0}, idx_diff_ys);
constexpr auto idx_diff_ps_ys = container_concat(
generate_tuple([&](auto) { return number<0>{}; }, number<NDimP>{}),
idx_diff_ys);
move_window_adaptor_and_bottom_tensor_thread_coordinate(
window_adaptor_thread_coord, bottom_tensor_thread_coord, idx_diff_ps_ys);
......@@ -565,8 +660,9 @@ struct tile_window_with_static_distribution
});
}
CK_TILE_DEVICE void
store_raw(const static_distributed_tensor<DataType, TileDstr>& dstr_tensor) const
template <index_t i_access_unsupport_ = -1>
CK_TILE_DEVICE void store_raw(const static_distributed_tensor<DataType, TileDstr>& dstr_tensor,
number<i_access_unsupport_> = {}) const
{
using Traits = load_store_traits;
......@@ -591,7 +687,7 @@ struct tile_window_with_static_distribution
// read from distributed tensor
vector_t vec_value;
static_for<0, Traits::ScalarPerVector, 1>{}([&](auto j) {
constexpr auto idx_ys = generate_array(
constexpr auto idx_ys = generate_tuple(
[&](auto jj) {
return jj == Traits::VectorDimY ? (idx_ys_start[jj] + j)
: idx_ys_start[jj];
......@@ -606,15 +702,16 @@ struct tile_window_with_static_distribution
// write into bottom tensor
get_bottom_tensor_view()
.template set_vectorized_elements_raw<vector_t, oob_conditional_check>(
bottom_tensor_thread_coord, vec_value);
bottom_tensor_thread_coord, 0, vec_value);
// move thread coordinate
if constexpr(iCoordAccess != (NumAccessPerCoord - 1))
{
constexpr auto idx_diff_ys = SFC_Ys::get_forward_step(iAccess);
constexpr auto idx_diff_ps_ys =
container_concat(array<index_t, NDimP>{0}, idx_diff_ys);
constexpr auto idx_diff_ps_ys = container_concat(
generate_tuple([&](auto) { return number<0>{}; }, number<NDimP>{}),
idx_diff_ys);
move_window_adaptor_and_bottom_tensor_thread_coordinate(
window_adaptor_thread_coord, bottom_tensor_thread_coord, idx_diff_ps_ys);
......@@ -623,8 +720,9 @@ struct tile_window_with_static_distribution
});
}
template <bool oob_conditional_check = true>
template <index_t i_access_unsupport_ = -1, bool oob_conditional_check = true>
CK_TILE_DEVICE void update(const static_distributed_tensor<DataType, TileDstr>& dstr_tensor,
number<i_access_unsupport_> = {},
bool_constant<oob_conditional_check> = {}) const
{
using Traits = load_store_traits;
......@@ -650,7 +748,7 @@ struct tile_window_with_static_distribution
vector_t vec_value;
static_for<0, Traits::ScalarPerVector, 1>{}([&](auto j) {
constexpr auto idx_ys = generate_array(
constexpr auto idx_ys = generate_tuple(
[&](auto jj) {
return jj == Traits::VectorDimY ? (idx_ys_start[jj] + j)
: idx_ys_start[jj];
......@@ -666,15 +764,19 @@ struct tile_window_with_static_distribution
// write into bottom tensor
get_bottom_tensor_view().template update_vectorized_elements<vector_t>(
bottom_tensor_thread_coord, vec_value, bool_constant<oob_conditional_check>{});
bottom_tensor_thread_coord,
0,
vec_value,
bool_constant<oob_conditional_check>{});
// move thread coordinate
if constexpr(iCoordAccess != (NumAccessPerCoord - 1))
{
constexpr auto idx_diff_ys = SFC_Ys::get_forward_step(iAccess);
constexpr auto idx_diff_ps_ys =
container_concat(array<index_t, NDimP>{0}, idx_diff_ys);
constexpr auto idx_diff_ps_ys = container_concat(
generate_tuple([&](auto) { return number<0>{}; }, number<NDimP>{}),
idx_diff_ys);
move_window_adaptor_and_bottom_tensor_thread_coordinate(
window_adaptor_thread_coord, bottom_tensor_thread_coord, idx_diff_ps_ys);
......@@ -746,7 +848,8 @@ struct tile_window_with_static_distribution
constexpr auto idx_diff_ys =
SFC_Ys::get_step_between(number<0>{}, number<iCoord * NumAccessPerCoord>{});
constexpr auto idx_diff_ps_ys = container_concat(array<index_t, NDimP>{0}, idx_diff_ys);
constexpr auto idx_diff_ps_ys = container_concat(
generate_tuple([&](auto) { return number<0>{}; }, number<NDimP>{}), idx_diff_ys);
move_window_adaptor_and_bottom_tensor_thread_coordinate(
window_adaptor_thread_coord, bottom_tensor_thread_coord, idx_diff_ps_ys);
......@@ -798,6 +901,27 @@ make_tile_window(const TensorView_& tensor_view,
tensor_view, window_lengths, origin, tile_distribution};
}
// this version can't be called in a constexpr context
template <typename TensorView_,
typename WindowLengths_,
typename StaticTileDistribution_,
index_t NumCoord = 1>
CK_TILE_DEVICE auto
make_tile_window_raw(const TensorView_& tensor_view,
const WindowLengths_& window_lengths,
const multi_index<TensorView_::get_num_of_dimension()>& origin,
const StaticTileDistribution_& tile_distribution,
number<NumCoord> = {})
{
auto w = tile_window_with_static_distribution<remove_cvref_t<TensorView_>,
remove_cvref_t<WindowLengths_>,
remove_cvref_t<StaticTileDistribution_>,
NumCoord>{
tensor_view, window_lengths, origin, tile_distribution};
w.init_raw();
return w;
}
template <typename TensorView_,
typename WindowLengths_,
typename StaticTileDistribution_,
......@@ -922,6 +1046,19 @@ make_tile_window(const tile_window_with_static_lengths<TensorView, WindowLengths
tile_distribution);
}
template <typename TensorView, typename WindowLengths, typename StaticTileDistribution>
CK_TILE_DEVICE constexpr auto
make_tile_window_raw(const tile_window_with_static_lengths<TensorView, WindowLengths>& tile_window,
const StaticTileDistribution& tile_distribution)
{
auto w = make_tile_window(tile_window.get_bottom_tensor_view(),
tile_window.get_window_lengths(),
tile_window.get_window_origin(),
tile_distribution);
w.init_raw();
return w;
}
template <typename TensorView_, typename WindowLengths_>
CK_TILE_DEVICE void move_tile_window(
tile_window_with_static_lengths<TensorView_, WindowLengths_>& window,
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core/arch/arch.hpp"
#include "ck_tile/core/arch/utility.hpp"
#include "ck_tile/core/algorithm/space_filling_curve.hpp"
#include "ck_tile/core/config.hpp"
#include "ck_tile/core/container/array.hpp"
#include "ck_tile/core/container/sequence.hpp"
#include "ck_tile/core/container/tuple.hpp"
#include "ck_tile/core/container/container_helper.hpp"
#include "ck_tile/core/tensor/static_distributed_tensor.hpp"
#include "ck_tile/core/tensor/tensor_adaptor.hpp"
#include "ck_tile/core/tensor/tile_distribution.hpp"
#include "ck_tile/core/utility/functional.hpp"
#include "ck_tile/core/utility/type_traits.hpp"
namespace ck_tile {
#define WINDOW_DISPATCH_ISSUE() \
if constexpr(i_access < 0) \
{ \
static_for<0, NumAccess, 1>{}([&](auto ia) { issue(ia); }); \
} \
else \
{ \
static_assert(i_access < NumAccess); \
issue(number<i_access>{}); \
}
//
// This version of tile window will pre-cache offset/flags based on need
//
// LinearBottomDims_, e.g seq<0, 1> for 2d tensor, the last one is linear dim
// so last dim can use immediate offset to indexing, can save register
// TODO: if using this struct, better use load_raw()/store_raw(), can control
// the the immediate offset on the fly
// space-filing-curve is non-snaked here!
//
template <typename BottomTensorView_,
typename WindowLengths_,
typename StaticTileDistribution_,
typename LinearBottomDims_>
struct tile_window_linear
{
using BottomTensorView = remove_reference_t<BottomTensorView_>;
using WindowLengths = remove_cvref_t<WindowLengths_>;
using TileDstr = remove_cvref_t<StaticTileDistribution_>;
using WindowAdaptor = typename TileDstr::PsYs2XsAdaptor;
using BottomTensorDesc = typename BottomTensorView::TensorDesc;
using DataType = remove_cvref_t<typename BottomTensorView::DataType>;
using LinearBottomDims = remove_cvref_t<LinearBottomDims_>;
static_assert(LinearBottomDims::size() == BottomTensorView::get_num_of_dimension());
static constexpr index_t NDimWindowAdaptorTop = WindowAdaptor::get_num_of_top_dimension();
static constexpr index_t NDimBottomTensor = BottomTensorDesc::get_num_of_dimension();
static constexpr index_t NDimP = TileDstr::get_num_of_dimension_p();
static constexpr index_t NDimY = TileDstr::get_num_of_dimension_y();
static constexpr auto I0 = number<0>{};
static constexpr auto I1 = number<1>{};
// TODO: check WindowLengths and StaticTileDistribution are consistent
static_assert(ck_tile::is_known_at_compile_time<WindowLengths>::value,
"wrong! lengths should be static");
static_assert(TileDstr::is_static(), "wrong!");
static_assert(NDimBottomTensor == WindowAdaptor::get_num_of_bottom_dimension(),
"wrong! inconsistent # of diemsnions");
using AdaptorTopIndex = array<index_t, NDimWindowAdaptorTop>;
using BottomTensorIndex = array<index_t, NDimBottomTensor>;
using WindowAdaptorCoord =
decltype(make_tensor_adaptor_coordinate(WindowAdaptor{}, AdaptorTopIndex{}));
using BottomTensorCoord =
decltype(make_tensor_coordinate(BottomTensorDesc{}, BottomTensorIndex{}));
struct traits
{
private:
// return vector dimension among [y0, y1, ...]
CK_TILE_DEVICE static constexpr auto get_window_adaptor_ys_safe_vector_length_strides()
{
// bottom tensor top dimension vector lengths and strides
const auto [bottom_tensor_top_dim_vector_lengths,
bottom_tensor_top_dim_vector_strides] =
BottomTensorDesc::get_top_dimension_safe_vector_length_strides();
// window vector lengths/strides
const auto window_adaptor_bottom_dim_vector_lengths =
bottom_tensor_top_dim_vector_lengths;
const auto window_adaptor_bottom_dim_vector_strides =
bottom_tensor_top_dim_vector_strides;
// window adaptor [p0, p1, ..., y0, y1, ...]
array<index_t, WindowAdaptor::get_num_of_hidden_dimension()>
window_adaptor_vector_lengths{-1};
array<index_t, WindowAdaptor::get_num_of_hidden_dimension()>
window_adaptor_vector_strides{-1};
constexpr auto window_adaptor_bottom_dims =
WindowAdaptor::get_bottom_dimension_hidden_ids();
set_container_subset(window_adaptor_vector_lengths,
window_adaptor_bottom_dims,
window_adaptor_bottom_dim_vector_lengths);
set_container_subset(window_adaptor_vector_strides,
window_adaptor_bottom_dims,
window_adaptor_bottom_dim_vector_strides);
const auto [window_adaptor_ps_ys_vector_lengths, window_adaptor_ps_ys_vector_strides] =
WindowAdaptor{}.get_top_dimension_safe_vector_length_strides(
window_adaptor_vector_lengths, window_adaptor_vector_strides);
// [y0, y1, ...]
constexpr auto y_dims =
typename arithmetic_sequence_gen<TileDstr::get_num_of_dimension_p(),
NDimWindowAdaptorTop,
1>::type{};
return make_tuple(get_container_subset(window_adaptor_ps_ys_vector_lengths, y_dims),
get_container_subset(window_adaptor_ps_ys_vector_strides, y_dims));
}
static constexpr auto get_vector_dim_y_scalar_per_vector()
{
const auto [ys_vector_lengths, ys_vector_strides] =
get_window_adaptor_ys_safe_vector_length_strides();
index_t VectorDimY_ = 0;
index_t ScalarPerVector_ = 1;
for(index_t i = 0; i < NDimY; ++i)
{
if(ys_vector_strides[i] == 1 && ys_vector_lengths[i] > ScalarPerVector_)
{
ScalarPerVector_ = ys_vector_lengths[i];
VectorDimY_ = i;
}
}
return make_tuple(VectorDimY_, ScalarPerVector_);
}
public:
static constexpr index_t VectorDimY = get_vector_dim_y_scalar_per_vector().template at<0>();
static constexpr index_t ScalarPerVector =
get_vector_dim_y_scalar_per_vector().template at<1>();
using vector_t = thread_buffer<DataType, ScalarPerVector>;
private:
static constexpr auto scalars_per_access_ = [] {
constexpr auto scalars_per_access_arr = generate_array(
[&](auto i) { return (i == VectorDimY) ? ScalarPerVector : 1; }, number<NDimY>{});
/// TODO: add non-automatic storage argument support to macro TO_SEQUENCE()
constexpr auto NDimY_ = NDimY;
return TO_SEQUENCE(scalars_per_access_arr, NDimY_);
}();
static constexpr auto get_space_filling_curve()
{
constexpr auto thread_tensor_lengths_ys =
to_sequence(TileDstr{}.get_ys_to_d_descriptor().get_lengths());
// FIXME: need logic to judge dim access order
using DimAccessOrder = typename arithmetic_sequence_gen<0, NDimY, 1>::type;
return space_filling_curve<decltype(thread_tensor_lengths_ys),
DimAccessOrder,
decltype(scalars_per_access_),
false /*!!! no snaked curve! */>{};
}
public:
using SFC_Ys = decltype(get_space_filling_curve());
static constexpr index_t NumAccess = SFC_Ys::get_num_of_access();
static_assert(0 < NumAccess, "Wrong! NumAccess should be larger than 0");
private:
static constexpr auto get_num_non_linear_access()
{
constexpr auto sfc_access_lens = SFC_Ys::access_lengths;
using ys_to_rhs_major =
typename decltype(TileDstr{}.get_static_tile_distribution_encoding())::Ys2RHsMajor;
constexpr auto non_linear = [&]() {
index_t cnt = 1;
static_for<0, NDimY, 1>{}([&](auto i_dim_y) {
constexpr auto rhs_major = ys_to_rhs_major{}[i_dim_y];
constexpr auto target_h_dim = number<rhs_major - 1>{}; // no r dim here!
if constexpr(LinearBottomDims{}[target_h_dim] == 0)
{
cnt *= sfc_access_lens[i_dim_y];
}
});
return cnt;
}();
return non_linear;
}
// example:
// non_linear_access_map: sequence<0, 0, 0, 0, 1, 1, 1, 1> for 8 access, totally 2 register
// used
// -> histogram : sequence<4, 4>
// -> prefixsum : seqneuce<0, 4, 8>
// non_linear_access_map: sequence<0, 1, 2, 3, 4, 5, 6, 7> for 8 access, totally 8 register
// used, will pre-cache 8
// -> histogram : sequence<1, 1, 1, 1, 1, 1, 1, 1>
// -> prefixsum : seqneuce<0, 1, 2, 3, 4, 5, 6, 7, 8>
// non_linear_access_map: sequence<0, 0, 1, 1, 2, 2, 3, 3> for 8 access, totally 4 register
// used, will pre-cache 4
// -> histogram : sequence<2, 2, 2, 2>
// -> prefixsum : seqneuce<0, 2, 4, 6, 8>
static constexpr auto get_non_linear_access_map()
{
constexpr auto sfc_access_lens = SFC_Ys::access_lengths;
using ys_to_rhs_major =
typename decltype(TileDstr{}.get_static_tile_distribution_encoding())::Ys2RHsMajor;
constexpr auto non_linear_map = [&]() {
array<index_t, NumAccess> m_{0};
index_t cumulative_len_ = 1;
index_t cumulative_non_linear_len_ = 1;
static_for<0, NDimY, 1>{}([&](auto i_y) {
constexpr auto i_dim_y = number<NDimY - i_y - 1>{}; // from right to left
constexpr auto rhs_major = ys_to_rhs_major{}[i_dim_y];
constexpr auto target_h_dim = number<rhs_major - 1>{}; // no r dim here!
constexpr auto is_linear_dim = LinearBottomDims{}[target_h_dim];
array<index_t, NumAccess> current_m_{0};
constexpr auto current_len_ = sfc_access_lens[i_dim_y];
// copy cumulative length as current pattern
for(auto i_ = 0; i_ < cumulative_len_; i_++)
{
current_m_(i_) = m_[i_];
}
for(auto j_ = 0; j_ < current_len_; j_++)
{
auto j_offset_ = is_linear_dim ? 0 : j_ * cumulative_non_linear_len_;
for(auto i_ = 0; i_ < cumulative_len_; i_++)
{
m_(j_ * cumulative_len_ + i_) = current_m_[i_] + j_offset_;
}
}
cumulative_len_ *= current_len_;
if(!is_linear_dim)
cumulative_non_linear_len_ *= current_len_;
});
return m_;
}();
return TO_SEQUENCE(non_linear_map, NumAccess);
}
static constexpr auto get_non_linear_access_histogram()
{
constexpr auto m_ = get_non_linear_access_map();
// m_.foo();
constexpr auto r_ =
typename arithmetic_sequence_gen<0, get_num_non_linear_access() + 1, 1>::type{};
constexpr auto h_ = histogram_sorted_sequence(m_, r_);
return h_;
}
static constexpr auto get_non_linear_access_histogram_prefix_sum()
{
constexpr auto h_ = get_non_linear_access_histogram();
constexpr auto h_prefix_sum_ = prefix_sum_sequence(h_);
return h_prefix_sum_;
}
public:
static constexpr index_t NumAccess_NonLinear = get_num_non_linear_access();
using AccessMap_NonLinear = decltype(get_non_linear_access_map()); // sequence
using AccessHistogram_NonLinear = decltype(get_non_linear_access_histogram());
using AccessPrefixSum_NonLinear = decltype(get_non_linear_access_histogram_prefix_sum());
};
static constexpr index_t NumAccess = traits::NumAccess;
static constexpr index_t NumAccess_NonLinear = traits::NumAccess_NonLinear;
using AccessMap_NonLinear = typename traits::AccessMap_NonLinear;
using AccessHistogram_NonLinear = typename traits::AccessHistogram_NonLinear;
using AccessPrefixSum_NonLinear = typename traits::AccessPrefixSum_NonLinear;
CK_TILE_DEVICE constexpr tile_window_linear() = default;
CK_TILE_DEVICE constexpr tile_window_linear(const BottomTensorView& bottom_tensor_view,
const WindowLengths& window_lengths,
const BottomTensorIndex& window_origin,
const TileDstr& tile_distribution)
: bottom_tensor_view_{bottom_tensor_view},
window_lengths_{window_lengths},
window_origin_{window_origin},
tile_dstr_{tile_distribution},
cached_coords_{},
cached_flags_{}
{
auto window_adaptor_thread_coord_tmp = make_tensor_adaptor_coordinate(
tile_distribution.get_ps_ys_to_xs_adaptor(),
container_concat(make_tuple(get_warp_id(), get_lane_id()),
generate_tuple([&](auto) { return number<0>{}; }, number<NDimY>{})));
BottomTensorIndex bottom_tensor_thread_origin_idx_tmp =
window_origin + window_adaptor_thread_coord_tmp.get_bottom_index();
auto bottom_tensor_thread_coord_tmp = make_tensor_coordinate(
bottom_tensor_view_.get_tensor_descriptor(), bottom_tensor_thread_origin_idx_tmp);
// future load/store() calls (might allocate more registers)
using SFC_Ys = typename traits::SFC_Ys;
static_for<0, NumAccess, 1>{}([&](auto i_access) {
constexpr auto non_linear_id = number<AccessMap_NonLinear{}[i_access]>{};
constexpr auto need_save_non_linear_coord =
bool_constant<AccessPrefixSum_NonLinear{}[non_linear_id] == i_access>{};
if constexpr(need_save_non_linear_coord)
{
cached_coords_(non_linear_id) = bottom_tensor_thread_coord_tmp;
}
// TODO: need pad_tensor_view to check which dim need use flag to check
// cached flag is independent from non-linear-coord
// but need be updated in move_tile, with proper dims
cached_flags_(i_access) = coordinate_has_valid_offset_assuming_top_index_is_valid(
bottom_tensor_view_.get_tensor_descriptor(), bottom_tensor_thread_coord_tmp);
if constexpr(i_access != (NumAccess - 1))
{
constexpr auto idx_diff_ys = SFC_Ys::get_forward_step(i_access); // tuple of number
constexpr auto idx_diff_ps_ys = container_concat(
generate_tuple([&](auto) { return number<0>{}; }, number<NDimP>{}),
idx_diff_ys);
move_window_adaptor_and_bottom_tensor_thread_coordinate(
window_adaptor_thread_coord_tmp,
bottom_tensor_thread_coord_tmp,
idx_diff_ps_ys);
}
});
}
CK_TILE_DEVICE static constexpr index_t get_num_of_dimension() { return NDimBottomTensor; }
CK_TILE_DEVICE static constexpr bool has_static_tile_distribution()
{
return TileDstr::is_static();
}
CK_TILE_DEVICE constexpr auto get_window_lengths() const { return window_lengths_; }
CK_TILE_DEVICE constexpr auto get_tile_distribution() const { return tile_dstr_; }
CK_TILE_DEVICE constexpr auto get_bottom_tensor_view() const { return bottom_tensor_view_; }
CK_TILE_DEVICE constexpr auto get_window_origin() const { return window_origin_; }
CK_TILE_DEVICE constexpr void
set_bottom_tensor_view_data_ptr(typename BottomTensorView::DataType* data)
{
bottom_tensor_view_.buf_.p_data_ = data;
}
// move thread's window adaptor coordinate and bottom tensor coordinate
// [p0, p1, ..., y0, y1, ...] ==> [x0, x1, ...] ==> [x0', x1', ...] ==> [offset]
template <typename ATopIndex>
CK_TILE_DEVICE void move_window_adaptor_and_bottom_tensor_thread_coordinate(
WindowAdaptorCoord& window_adaptor_thread_coord,
BottomTensorCoord& bottom_tensor_thread_coord,
const ATopIndex& idx_diff_adaptor_top) const
{
array<index_t, NDimBottomTensor> idx_diff_adaptor_bottom;
move_tensor_adaptor_coordinate(tile_dstr_.get_ps_ys_to_xs_adaptor(),
window_adaptor_thread_coord,
idx_diff_adaptor_top,
idx_diff_adaptor_bottom);
move_tensor_coordinate(bottom_tensor_view_.get_tensor_descriptor(),
bottom_tensor_thread_coord,
idx_diff_adaptor_bottom);
}
template <index_t i_access>
CK_TILE_DEVICE static constexpr auto get_bottom_linear_coordinate(number<i_access>)
{
using SFC_Ys = typename traits::SFC_Ys;
constexpr auto idx_ys = SFC_Ys::get_index(number<i_access>{});
using ys_to_rhs_major =
typename decltype(TileDstr{}.get_static_tile_distribution_encoding())::Ys2RHsMajor;
constexpr auto modified_idx_ys = generate_tuple(
[&](auto i_dim_y) {
constexpr auto rhs_major = ys_to_rhs_major{}[i_dim_y];
constexpr auto target_h_dim = number<rhs_major - 1>{}; // no r dim here!
if constexpr(LinearBottomDims{}[target_h_dim] == 0)
{
return number<0>{};
}
else
{
return number<idx_ys[i_dim_y]>{};
}
},
number<NDimY>{});
constexpr auto adaptor_ = TileDstr{}.get_ps_ys_to_xs_adaptor();
constexpr auto idx_ =
container_concat(make_tuple(number<0>{}, number<0>{}), modified_idx_ys);
return adaptor_.calculate_bottom_index(idx_);
}
template <index_t i_access>
CK_TILE_DEVICE static constexpr index_t get_bottom_linear_offset(number<i_access>)
{
constexpr auto linear_coord = get_bottom_linear_coordinate(number<i_access>{});
// since this is linear offset, we assum bottom X tensor is always linear
constexpr index_t linear_offset = [&]() {
constexpr auto x_idx_ = linear_coord;
constexpr auto x_len_ = TileDstr{}.get_lengths();
static_assert(x_idx_.size() == x_len_.size());
constexpr index_t x_dims_ = x_idx_.size();
index_t cu_stride_ = 1;
index_t cu_offset_ = 0;
static_for<0, x_dims_, 1>{}([&](auto i_) {
auto r_i_ = number<x_dims_ - i_ - 1>{};
cu_offset_ += x_idx_[r_i_] * cu_stride_;
cu_stride_ *= x_len_[r_i_];
});
return cu_offset_;
}();
return linear_offset;
}
CK_TILE_DEVICE constexpr auto get_num_of_access() const { return traits::NumAccess; }
template <index_t i_access = -1, bool oob_conditional_check = true>
CK_TILE_DEVICE auto load(number<i_access> = {}, bool_constant<oob_conditional_check> = {}) const
{
using vector_t = typename traits::vector_t;
using SFC_Ys = typename traits::SFC_Ys;
constexpr auto tile_dstr = TileDstr{};
auto dst_tensor = make_static_distributed_tensor<DataType>(tile_dstr);
auto issue = [&](auto i_access_) {
constexpr auto IAccess = number<i_access_>{};
constexpr auto non_linear_id = number<AccessMap_NonLinear{}[IAccess]>{};
auto bottom_tensor_thread_coord = cached_coords_[non_linear_id];
auto bottom_tensor_flag = cached_flags_[IAccess];
constexpr auto linear_offset = get_bottom_linear_offset(IAccess);
// read from bottom tensor
const vector_t vec_value =
get_bottom_tensor_view().template get_vectorized_elements<vector_t>(
bottom_tensor_thread_coord,
linear_offset,
bottom_tensor_flag,
bool_constant<oob_conditional_check>{});
#if 1
// data index [y0, y1, ...]
constexpr auto idx_diff_ys = SFC_Ys::get_index(IAccess);
// write into distributed tensor
static_for<0, traits::ScalarPerVector, 1>{}([&](auto j) {
constexpr auto idx_ys = generate_tuple(
[&](auto jj) {
return jj == traits::VectorDimY ? (idx_diff_ys[jj] + j) : idx_diff_ys[jj];
},
number<NDimY>{});
constexpr index_t d = tile_dstr.get_ys_to_d_descriptor().calculate_offset(idx_ys);
dst_tensor.get_thread_buffer().template at<d>() =
vec_value.template get_as<DataType>()[j];
});
#else
constexpr index_t d = tile_dstr.get_ys_to_d_descriptor().calculate_offset(idx_ys_start);
static_assert(d % traits::ScalarPerVector == 0);
dst_tensor.get_thread_buffer().template get_as<vector_t>()(
number<d / traits::ScalarPerVector>{}) = bit_cast<vector_t>(vec_value);
#endif
};
WINDOW_DISPATCH_ISSUE();
return dst_tensor;
}
template <typename DstTile,
index_t i_access = -1,
bool oob_conditional_check = true,
bool pre_nop = false>
CK_TILE_DEVICE void load_raw(DstTile& dst_tensor,
number<i_access> = {}, // negative means loop over all num_access
bool_constant<oob_conditional_check> = {},
bool_constant<pre_nop> = {}) const
{
using vector_t = typename traits::vector_t;
using SFC_Ys = typename traits::SFC_Ys;
static constexpr index_t YElementSize =
TileDstr{}.get_ys_to_d_descriptor().get_element_space_size();
static_assert(YElementSize % traits::ScalarPerVector == 0);
using vectorized_tbuf = array<vector_t, YElementSize / traits::ScalarPerVector>;
constexpr auto tile_dstr = TileDstr{};
auto& dst_vec_tbuf = reinterpret_cast<vectorized_tbuf&>(dst_tensor.get_thread_buffer());
auto issue = [&](auto i_access_) {
constexpr auto IAccess = number<i_access_>{};
constexpr auto pre_nop_ = [&]() {
if constexpr(pre_nop && i_access_ == 0 &&
BottomTensorView::buffer_view::get_address_space() ==
address_space_enum::global)
return bool_constant<true>{};
else
return bool_constant<false>{};
}();
constexpr auto non_linear_id = number<AccessMap_NonLinear{}[IAccess]>{};
auto bottom_tensor_thread_coord = cached_coords_[non_linear_id];
constexpr auto linear_offset = get_bottom_linear_offset(IAccess);
auto bottom_tensor_flag = cached_flags_[IAccess];
// data index [y0, y1, ...]
constexpr auto idx_ys_start = SFC_Ys::get_index(IAccess);
constexpr index_t d = tile_dstr.get_ys_to_d_descriptor().calculate_offset(idx_ys_start);
static_assert(d % traits::ScalarPerVector == 0);
get_bottom_tensor_view().template get_vectorized_elements_raw<vector_t>(
dst_vec_tbuf.template at<d / traits::ScalarPerVector>(),
bottom_tensor_thread_coord,
linear_offset /**/,
bottom_tensor_flag,
bool_constant<oob_conditional_check>{},
pre_nop_);
#if CK_TILE_WORKAROUND_ROCM_6_1_SCRATCH_MEMORY_ISSUE || \
CK_TILE_WORKAROUND_ROCM_6_2_SCRATCH_MEMORY_ISSUE
asm volatile(""); // this is starting from rocm-6.2, but same sympton, reuse this flag
#endif
};
WINDOW_DISPATCH_ISSUE();
}
// TODO: currently async load only implemented in inline asm
template <typename LdsTileWindow_,
index_t i_access = -1,
bool oob_conditional_check = true,
bool pre_nop = false>
CK_TILE_DEVICE auto async_load_raw(LdsTileWindow_&& lds_tile,
number<i_access> = {},
bool_constant<oob_conditional_check> = {},
bool_constant<pre_nop> = {}) const
{
using LdsTileWindow = remove_cvref_t<LdsTileWindow_>;
using LdsDataType = typename LdsTileWindow::DataType;
// currently we only support everything is non linear dim
// actually it's not performant if we have linear dim(e.g. fast changing)
static_assert(NumAccess_NonLinear == NumAccess);
static_assert(BottomTensorView::buffer_view::get_address_space() ==
address_space_enum::global);
// issues * warps * lanes
static_assert(LdsTileWindow::get_num_of_dimension() == 3); // TODO: hard coded
const index_t size_per_buf =
lds_tile.get_bottom_tensor_view().get_tensor_descriptor().calculate_offset(
make_tuple(number<0>{}, number<0>{}, number<0>{})) *
sizeof(LdsDataType);
const index_t size_per_wave =
lds_tile.get_bottom_tensor_view().get_tensor_descriptor().calculate_offset(
make_tuple(number<0>{}, number<1>{}, number<0>{})) *
sizeof(LdsDataType) -
size_per_buf;
const index_t size_per_issue =
lds_tile.get_bottom_tensor_view().get_tensor_descriptor().calculate_offset(
make_tuple(number<1>{}, number<0>{}, number<0>{})) *
sizeof(LdsDataType) -
size_per_buf;
const index_t m0_init_value = size_per_buf + size_per_wave * get_warp_id();
m0_set_with_memory(m0_init_value); // This should be wave independent
using vector_t = typename traits::vector_t;
LdsDataType* smem = lds_tile.get_bottom_tensor_view().get_buffer_view().p_data_;
// loop over thread tensor space [y0, y1, ...]
auto issue = [&](auto i_access_) {
constexpr auto IAccess = number<i_access_>{};
constexpr auto pre_nop_ = [&]() {
if constexpr(pre_nop && i_access_ == 0)
return bool_constant<true>{};
else
return bool_constant<false>{};
}();
constexpr auto non_linear_id = number<AccessMap_NonLinear{}[IAccess]>{};
auto bottom_tensor_thread_coord = cached_coords_[non_linear_id];
auto bottom_tensor_flag = cached_flags_[IAccess]; // get this flag anyway
// read from bottom tensor
get_bottom_tensor_view().template async_get_vectorized_elements_raw<vector_t>(
smem, bottom_tensor_thread_coord, 0, bottom_tensor_flag, pre_nop_);
// move thread coordinate
if constexpr(i_access_ != (NumAccess - 1))
{
m0_inc_with_memory(size_per_issue);
}
};
WINDOW_DISPATCH_ISSUE();
}
template <typename LdsTileWindow_, index_t i_access = -1, bool oob_conditional_check = true>
CK_TILE_DEVICE auto async_load(LdsTileWindow_&& lds_tile,
number<i_access> = {},
bool_constant<oob_conditional_check> = {}) const
{
using LdsTileWindow = remove_cvref_t<LdsTileWindow_>;
using LdsDataType = typename LdsTileWindow::DataType;
// currently we only support everything is non linear dim
// actually it's not performant if we have linear dim(e.g. fast changing)
static_assert(NumAccess_NonLinear == NumAccess);
static_assert(BottomTensorView::buffer_view::get_address_space() ==
address_space_enum::global);
// issues * warps * lanes
static_assert(LdsTileWindow::get_num_of_dimension() == 3); // TODO: hard coded
// TODO: LDS offset is not good for intrinsic based implementation(compiler can't figure out
// dependency) hence avoid use offset based solution. size_per_buf should be zero (how to
// check?)
constexpr index_t size_per_buf =
lds_tile.get_bottom_tensor_view().get_tensor_descriptor().calculate_offset(
make_tuple(number<0>{}, number<0>{}, number<0>{}));
constexpr index_t size_per_wave =
lds_tile.get_bottom_tensor_view().get_tensor_descriptor().calculate_offset(
make_tuple(number<0>{}, number<1>{}, number<0>{})) -
size_per_buf;
constexpr index_t size_per_issue =
lds_tile.get_bottom_tensor_view().get_tensor_descriptor().calculate_offset(
make_tuple(number<1>{}, number<0>{}, number<0>{})) -
size_per_buf;
const index_t m0_init_value = size_per_buf + size_per_wave * get_warp_id();
using vector_t = typename traits::vector_t;
// TODO: we force CK_TILE_LDS_ADDR
CK_TILE_LDS_ADDR LdsDataType* smem =
lds_tile.get_bottom_tensor_view().get_buffer_view().p_data_ + m0_init_value;
// loop over thread tensor space [y0, y1, ...]
auto issue = [&](auto i_access_) {
constexpr auto IAccess = number<i_access_>{};
constexpr auto non_linear_id = number<AccessMap_NonLinear{}[IAccess]>{};
auto bottom_tensor_thread_coord = cached_coords_[non_linear_id];
auto bottom_tensor_flag = cached_flags_[IAccess];
// read from bottom tensor
get_bottom_tensor_view().template async_get_vectorized_elements<vector_t>(
smem,
bottom_tensor_thread_coord,
0,
bottom_tensor_flag,
bool_constant<oob_conditional_check>{});
// move thread coordinate
if constexpr(i_access_ != (NumAccess - 1))
{
smem += size_per_issue; // Note we manually increase the per-issue offset
}
};
WINDOW_DISPATCH_ISSUE();
}
template <index_t i_access = -1, bool oob_conditional_check = true>
CK_TILE_DEVICE void store(const static_distributed_tensor<DataType, TileDstr>& dstr_tensor,
number<i_access> = {},
bool_constant<oob_conditional_check> = {}) const
{
using vector_t = typename traits::vector_t;
using SFC_Ys = typename traits::SFC_Ys;
constexpr auto tile_dstr = TileDstr{};
// loop over thread tensor space [y0, y1, ...]
auto issue = [&](auto i_access_) {
constexpr auto IAccess = number<i_access_>{};
constexpr auto non_linear_id = number<AccessMap_NonLinear{}[IAccess]>{};
auto bottom_tensor_thread_coord = cached_coords_[non_linear_id];
constexpr auto linear_offset = get_bottom_linear_offset(IAccess);
auto bottom_tensor_flag = cached_flags_[IAccess];
// data index [y0, y1, ...]
constexpr auto idx_ys_start = SFC_Ys::get_index(IAccess);
// read from distributed tensor
vector_t vec_value;
static_for<0, traits::ScalarPerVector, 1>{}([&](auto j) {
constexpr auto idx_ys = generate_tuple(
[&](auto jj) {
return jj == traits::VectorDimY ? (idx_ys_start[jj] + j) : idx_ys_start[jj];
},
number<NDimY>{});
constexpr index_t d = tile_dstr.get_ys_to_d_descriptor().calculate_offset(idx_ys);
vec_value.template get_as<DataType>()(j) =
dstr_tensor.get_thread_buffer().template at<d>();
});
// write into bottom tensor
get_bottom_tensor_view().template set_vectorized_elements<vector_t>(
bottom_tensor_thread_coord,
linear_offset,
bottom_tensor_flag,
vec_value,
bool_constant<oob_conditional_check>{});
};
WINDOW_DISPATCH_ISSUE();
}
template <index_t i_access = -1>
CK_TILE_DEVICE void store_raw(const static_distributed_tensor<DataType, TileDstr>& dstr_tensor,
number<i_access> = {}) const
{
using vector_t = typename traits::vector_t;
using SFC_Ys = typename traits::SFC_Ys;
constexpr auto tile_dstr = TileDstr{};
static constexpr bool oob_conditional_check = true;
// loop over thread tensor space [y0, y1, ...]
auto issue = [&](auto i_access_) {
constexpr auto IAccess = number<i_access_>{};
constexpr auto non_linear_id = number<AccessMap_NonLinear{}[IAccess]>{};
auto bottom_tensor_thread_coord = cached_coords_[non_linear_id];
constexpr auto linear_offset = get_bottom_linear_offset(IAccess);
auto bottom_tensor_flag = cached_flags_[IAccess];
// data index [y0, y1, ...]
constexpr auto idx_ys_start = SFC_Ys::get_index(IAccess);
// read from distributed tensor
vector_t vec_value;
static_for<0, traits::ScalarPerVector, 1>{}([&](auto j) {
constexpr auto idx_ys = generate_tuple(
[&](auto jj) {
return jj == traits::VectorDimY ? (idx_ys_start[jj] + j) : idx_ys_start[jj];
},
number<NDimY>{});
constexpr index_t d = tile_dstr.get_ys_to_d_descriptor().calculate_offset(idx_ys);
vec_value.template get_as<DataType>()(j) =
dstr_tensor.get_thread_buffer().template at<d>();
});
// write into bottom tensor
get_bottom_tensor_view()
.template set_vectorized_elements_raw<vector_t, oob_conditional_check>(
bottom_tensor_thread_coord, linear_offset, bottom_tensor_flag, vec_value);
};
WINDOW_DISPATCH_ISSUE();
}
template <index_t i_access = -1, bool oob_conditional_check = true>
CK_TILE_DEVICE void update(const static_distributed_tensor<DataType, TileDstr>& dstr_tensor,
number<i_access> = {},
bool_constant<oob_conditional_check> = {}) const
{
using vector_t = typename traits::vector_t;
using SFC_Ys = typename traits::SFC_Ys;
constexpr auto tile_dstr = TileDstr{};
// loop over thread tensor space [y0, y1, ...]
auto issue = [&](auto i_access_) {
constexpr auto IAccess = number<i_access_>{};
constexpr auto non_linear_id = number<AccessMap_NonLinear{}[IAccess]>{};
auto bottom_tensor_thread_coord = cached_coords_[non_linear_id];
constexpr auto linear_offset = get_bottom_linear_offset(IAccess);
auto bottom_tensor_flag = cached_flags_[IAccess];
// data index [y0, y1, ...]
constexpr auto idx_ys_start = SFC_Ys::get_index(IAccess);
// read from distributed tensor
vector_t vec_value;
static_for<0, traits::ScalarPerVector, 1>{}([&](auto j) {
constexpr auto idx_ys = generate_tuple(
[&](auto jj) {
return jj == traits::VectorDimY ? (idx_ys_start[jj] + j) : idx_ys_start[jj];
},
number<NDimY>{});
constexpr index_t d = tile_dstr.get_ys_to_d_descriptor().calculate_offset(idx_ys);
vec_value.template get_as<DataType>()(j) =
dstr_tensor.get_thread_buffer().template at<d>();
});
// write into bottom tensor
get_bottom_tensor_view().template update_vectorized_elements<vector_t>(
bottom_tensor_thread_coord,
linear_offset,
bottom_tensor_flag,
vec_value,
bool_constant<oob_conditional_check>{});
};
WINDOW_DISPATCH_ISSUE();
}
// move thread's botom tensor coordiante
// [x0', x1', ... ] ==> [offset]
// also move window-origin
CK_TILE_DEVICE void move(const BottomTensorIndex& step)
{
window_origin_ += step;
static_for<0, NumAccess, 1>{}([&](auto i_access) {
constexpr auto IAccess = number<i_access>{};
constexpr auto non_linear_id = number<AccessMap_NonLinear{}[i_access]>{};
constexpr auto need_update_non_linear_coord =
bool_constant<AccessPrefixSum_NonLinear{}[non_linear_id] == i_access>{};
if constexpr(need_update_non_linear_coord)
{
move_tensor_coordinate(bottom_tensor_view_.get_tensor_descriptor(),
cached_coords_(non_linear_id),
step);
}
// move the current coord with linear_coords
auto tmp_coords = cached_coords_[non_linear_id];
constexpr auto linear_coord = get_bottom_linear_coordinate(IAccess);
move_tensor_coordinate(
bottom_tensor_view_.get_tensor_descriptor(), tmp_coords, linear_coord);
cached_flags_(IAccess) = coordinate_has_valid_offset_assuming_top_index_is_valid(
bottom_tensor_view_.get_tensor_descriptor(), tmp_coords);
});
}
CK_TILE_DEVICE void set_window_origin(const BottomTensorIndex& new_window_origin)
{
window_origin_ = new_window_origin;
auto window_adaptor_thread_coord_tmp = make_tensor_adaptor_coordinate(
TileDstr{}.get_ps_ys_to_xs_adaptor(),
container_concat(make_tuple(get_warp_id(), get_lane_id()),
generate_tuple([&](auto) { return number<0>{}; }, number<NDimY>{})));
BottomTensorIndex bottom_tensor_thread_origin_idx_tmp =
window_origin_ + window_adaptor_thread_coord_tmp.get_bottom_index();
auto bottom_tensor_thread_coord_tmp = make_tensor_coordinate(
bottom_tensor_view_.get_tensor_descriptor(), bottom_tensor_thread_origin_idx_tmp);
// future load/store() calls (might allocate more registers)
using SFC_Ys = typename traits::SFC_Ys;
static_for<0, NumAccess, 1>{}([&](auto i_access) {
constexpr auto non_linear_id = number<AccessMap_NonLinear{}[i_access]>{};
constexpr auto need_save_non_linear_coord =
bool_constant<AccessPrefixSum_NonLinear{}[non_linear_id] == i_access>{};
if constexpr(need_save_non_linear_coord)
{
cached_coords_(non_linear_id) = bottom_tensor_thread_coord_tmp;
}
if constexpr(i_access != (NumAccess - 1))
{
constexpr auto idx_diff_ys = SFC_Ys::get_forward_step(i_access); // tuple of number
constexpr auto idx_diff_ps_ys = container_concat(
generate_tuple([&](auto) { return number<0>{}; }, number<NDimP>{}),
idx_diff_ys);
move_window_adaptor_and_bottom_tensor_thread_coordinate(
window_adaptor_thread_coord_tmp,
bottom_tensor_thread_coord_tmp,
idx_diff_ps_ys);
}
});
}
CK_TILE_HOST_DEVICE void init_raw() { bottom_tensor_view_.init_raw(); }
// this is the bottom tensor view
// [x0', x1', ...] ==> [offset]
BottomTensorView bottom_tensor_view_;
//
WindowLengths window_lengths_;
// origin ([x0', x1', ...]) of window on bottom tensor
BottomTensorIndex window_origin_;
// Tile tensor distribution, which contains:
// 1. adaptor for window: [p0, p1, ..., y0, y1, ...] ==> [x0, x1, ...]
// 2. thread descriptor for thread tensor in register: [y0, y1, ...] ==> [d]
TileDstr tile_dstr_;
// this contains:
array<BottomTensorCoord, traits::NumAccess_NonLinear> cached_coords_;
array<bool, traits::NumAccess> cached_flags_;
};
#undef WINDOW_DISPATCH_ISSUE
namespace impl {
template <address_space_enum, index_t len_>
struct default_linear_bottom_dims_impl
{
using type = typename uniform_sequence_gen<len_, 0>::type;
};
template <index_t len_>
struct default_linear_bottom_dims_impl<address_space_enum::global, len_>
{
// global default to seq<0,0,....1>
using type = typename sequence_merge<typename uniform_sequence_gen<len_ - 1, 0>::type,
sequence<1>>::type;
};
template <index_t len_>
struct default_linear_bottom_dims_impl<address_space_enum::lds, len_>
{
// lds default to seq<1,1.....1>
using type = typename uniform_sequence_gen<len_, 1>::type;
};
} // namespace impl
template <typename TensorView_>
using default_linear_bottom_dims =
typename impl::default_linear_bottom_dims_impl<TensorView_::buffer_view::get_address_space(),
TensorView_::get_num_of_dimension()>::type;
// if using this API, will create a tile_window_linear
// this structure can have the chance to use immediate value, save register
// need pass in LinearBottomDims_ properly to control which dim is linear
// so to generate a constexpr offset as linear_offset for this dim
// (and finally pass to the immediate offset of buffer/lds instruction)
//
// Note: there is no internal check for which dim is OK to use linear offset
// user must make sure by themselves
//
// e.g.
// 2d global matrix, set LinearBottomDims_=seq<0, 1>, the last dim will generate
// immediate offset if each thread has multiple issue along last dim
//
// 2d LDS buffer, set LinearBottomDims_=seq<1, 1>, then only one vgpr used as offset
// everything else is just using immediate offset.
//
template <typename TensorView_,
typename WindowLengths_,
typename StaticTileDistribution_,
typename LinearBottomDims_ = default_linear_bottom_dims<TensorView_>>
CK_TILE_DEVICE constexpr auto
make_tile_window_linear(const TensorView_& tensor_view,
const WindowLengths_& window_lengths,
const multi_index<TensorView_::get_num_of_dimension()>& origin,
const StaticTileDistribution_& tile_distribution,
LinearBottomDims_ = {})
{
static_assert(LinearBottomDims_::size() == TensorView_::get_num_of_dimension());
return tile_window_linear<remove_cvref_t<TensorView_>,
remove_cvref_t<WindowLengths_>,
remove_cvref_t<StaticTileDistribution_>,
remove_cvref_t<LinearBottomDims_>>{
tensor_view, window_lengths, origin, tile_distribution};
}
template <
typename TileWindow_,
typename StaticTileDistribution_,
typename LinearBottomDims_ = default_linear_bottom_dims<typename TileWindow_::BottomTensorView>>
CK_TILE_DEVICE constexpr auto
make_tile_window_linear(const TileWindow_& tile_window,
const StaticTileDistribution_& tile_distribution,
LinearBottomDims_ = {})
{
return make_tile_window_linear(tile_window.get_bottom_tensor_view(),
tile_window.get_window_lengths(),
tile_window.get_window_origin(),
tile_distribution,
LinearBottomDims_{});
}
// this version must not be called under a constexpr context
template <typename TensorView_,
typename WindowLengths_,
typename StaticTileDistribution_,
typename LinearBottomDims_ = default_linear_bottom_dims<TensorView_>>
CK_TILE_DEVICE auto
make_tile_window_linear_raw(const TensorView_& tensor_view,
const WindowLengths_& window_lengths,
const multi_index<TensorView_::get_num_of_dimension()>& origin,
const StaticTileDistribution_& tile_distribution,
LinearBottomDims_ = {})
{
static_assert(LinearBottomDims_::size() == TensorView_::get_num_of_dimension());
auto w = tile_window_linear<remove_cvref_t<TensorView_>,
remove_cvref_t<WindowLengths_>,
remove_cvref_t<StaticTileDistribution_>,
remove_cvref_t<LinearBottomDims_>>{
tensor_view, window_lengths, origin, tile_distribution};
w.init_raw();
return w;
}
template <
typename TileWindow_,
typename StaticTileDistribution_,
typename LinearBottomDims_ = default_linear_bottom_dims<typename TileWindow_::BottomTensorView>>
CK_TILE_DEVICE constexpr auto
make_tile_window_linear_raw(const TileWindow_& tile_window,
const StaticTileDistribution_& tile_distribution,
LinearBottomDims_ = {})
{
return make_tile_window_linear_raw(tile_window.get_bottom_tensor_view(),
tile_window.get_window_lengths(),
tile_window.get_window_origin(),
tile_distribution,
LinearBottomDims_{});
}
template <typename TensorView_,
typename WindowLengths_,
typename StaticTileDistribution_,
typename LinearBottomDims_>
CK_TILE_DEVICE void move_tile_window(
tile_window_linear<TensorView_, WindowLengths_, StaticTileDistribution_, LinearBottomDims_>&
window,
const typename tile_window_linear<TensorView_,
WindowLengths_,
StaticTileDistribution_,
LinearBottomDims_>::BottomTensorIndex& step)
{
window.move(step);
}
} // namespace ck_tile
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <cstdlib>
namespace ck_tile {
namespace literals {
// [P0330] Literal Suffix for (signed) size_t (C++23)
// ref: https://wg21.link/p0330r8
inline constexpr std::size_t operator""_uz(unsigned long long size)
{
return static_cast<std::size_t>(size);
}
inline constexpr std::size_t operator""_zu(unsigned long long size)
{
return static_cast<std::size_t>(size);
}
} // namespace literals
} // namespace ck_tile
......@@ -59,8 +59,16 @@ struct magic_division32_bit_range
CK_TILE_DEVICE static constexpr uint32_t
do_magic_division(uint32_t dividend, uint32_t multiplier, uint32_t shift)
{
uint32_t tmp = __umulhi(dividend, multiplier);
return (tmp + dividend) >> shift;
if(__builtin_is_constant_evaluated())
{
uint32_t tmp = (static_cast<uint64_t>(dividend) * multiplier) >> 32;
return (tmp + dividend) >> shift;
}
else
{
uint32_t tmp = __umulhi(dividend, multiplier);
return (tmp + dividend) >> shift;
}
}
CK_TILE_HOST static constexpr uint32_t
......@@ -77,9 +85,18 @@ struct magic_division32_bit_range
CK_TILE_DEVICE static constexpr int32_t
do_magic_division(int32_t dividend_i32, uint32_t multiplier, uint32_t shift)
{
uint32_t dividend_u32 = bit_cast<uint32_t>(dividend_i32);
uint32_t tmp = __umulhi(dividend_u32, multiplier);
return (tmp + dividend_u32) >> shift;
if(__builtin_is_constant_evaluated())
{
uint32_t dividend_u32 = bit_cast<uint32_t>(dividend_i32);
uint32_t tmp = (static_cast<uint64_t>(dividend_u32) * multiplier) >> 32;
return (tmp + dividend_u32) >> shift;
}
else
{
uint32_t dividend_u32 = bit_cast<uint32_t>(dividend_i32);
uint32_t tmp = __umulhi(dividend_u32, multiplier);
return (tmp + dividend_u32) >> shift;
}
}
CK_TILE_HOST static constexpr int32_t
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core/config.hpp"
namespace ck_tile {
namespace ReduceOp {
// y = ReduceOp(y, x);
struct Add
{
template <typename T>
CK_TILE_HOST_DEVICE static constexpr T GetIdentityValue()
{
return type_convert<T>(0.0f);
};
template <typename T,
typename = std::enable_if_t<std::is_same_v<T, float> || std::is_same_v<T, double> ||
std::is_same_v<T, int32_t> || std::is_same_v<T, int8_t>>>
CK_TILE_HOST_DEVICE constexpr T operator()(const T& y, const T x) const
{
return y + x;
}
template <typename T,
typename = std::enable_if_t<std::is_same_v<T, half_t> || std::is_same_v<T, bf16_t>>>
CK_TILE_HOST_DEVICE constexpr T operator()(T& y, T x) const
{
float y_ = type_convert<float>(y);
float x_ = type_convert<float>(x);
return type_convert<T>(y_ + x_);
}
};
struct SquareAdd
{
template <typename T>
CK_TILE_HOST_DEVICE static constexpr T GetIdentityValue()
{
return type_convert<T>(0.0f);
};
template <typename T,
typename = std::enable_if_t<std::is_same_v<T, float> || std::is_same_v<T, double> ||
std::is_same_v<T, int32_t> || std::is_same_v<T, int8_t>>>
CK_TILE_HOST_DEVICE constexpr T operator()(const T& y, const T x) const
{
return y + (x * x);
}
};
struct Max
{
template <typename T,
typename = std::enable_if_t<std::is_same_v<T, float> || std::is_same_v<T, double> ||
std::is_same_v<T, int32_t> || std::is_same_v<T, int8_t>>>
CK_TILE_HOST_DEVICE static constexpr T GetIdentityValue()
{
return numeric<T>::min();
};
template <typename T,
typename = std::enable_if_t<std::is_same_v<T, float> || std::is_same_v<T, double> ||
std::is_same_v<T, int32_t> || std::is_same_v<T, int8_t>>>
CK_TILE_HOST_DEVICE constexpr T operator()(const T& y, const T x) const
{
return max(y, x);
}
};
struct AbsMax
{
template <typename T,
typename = std::enable_if_t<std::is_same_v<T, float> || std::is_same_v<T, double> ||
std::is_same_v<T, int32_t> || std::is_same_v<T, int8_t>>>
CK_TILE_HOST_DEVICE static constexpr T GetIdentityValue()
{
return numeric<T>::min();
};
template <typename T,
typename = std::enable_if_t<std::is_same_v<T, float> || std::is_same_v<T, double> ||
std::is_same_v<T, int32_t> || std::is_same_v<T, int8_t>>>
CK_TILE_HOST_DEVICE constexpr T operator()(const T& y, const T x) const
{
return max(y, abs(x));
}
};
} // namespace ReduceOp
} // namespace ck_tile
......@@ -19,10 +19,15 @@
#include "ck_tile/host/reference/reference_batched_masking.hpp"
#include "ck_tile/host/reference/reference_batched_rotary_position_embedding.hpp"
#include "ck_tile/host/reference/reference_batched_softmax.hpp"
#include "ck_tile/host/reference/reference_elementwise.hpp"
#include "ck_tile/host/reference/reference_gemm.hpp"
#include "ck_tile/host/reference/reference_im2col.hpp"
#include "ck_tile/host/reference/reference_layernorm2d_fwd.hpp"
#include "ck_tile/host/reference/reference_permute.hpp"
#include "ck_tile/host/reference/reference_reduce.hpp"
#include "ck_tile/host/reference/reference_rmsnorm2d_fwd.hpp"
#include "ck_tile/host/reference/reference_rowwise_quantization2d.hpp"
#include "ck_tile/host/reference/reference_softmax.hpp"
#include "ck_tile/host/reference/reference_topk.hpp"
#include "ck_tile/host/stream_config.hpp"
#include "ck_tile/host/timer.hpp"
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