Commit d6a666fa authored by Rostyslav Geyyer's avatar Rostyslav Geyyer
Browse files

Put type_converts into a separate header

parent f61c7704
...@@ -5,6 +5,7 @@ ...@@ -5,6 +5,7 @@
#include "ck/utility/f8_utils.hpp" #include "ck/utility/f8_utils.hpp"
#include "ck/utility/statically_indexed_array.hpp" #include "ck/utility/statically_indexed_array.hpp"
#include "ck/utility/type_convert.hpp"
namespace ck { namespace ck {
...@@ -960,267 +961,6 @@ using f8x16_t = typename vector_type<f8_t, 16>::type; ...@@ -960,267 +961,6 @@ using f8x16_t = typename vector_type<f8_t, 16>::type;
using f8x32_t = typename vector_type<f8_t, 32>::type; using f8x32_t = typename vector_type<f8_t, 32>::type;
using f8x64_t = typename vector_type<f8_t, 64>::type; using f8x64_t = typename vector_type<f8_t, 64>::type;
// Convert X to Y
template <typename Y, typename X>
__host__ __device__ constexpr Y type_convert(X x)
{
static_assert(!std::is_reference_v<Y> && !std::is_reference_v<X>);
return static_cast<Y>(x);
}
// convert bfp16 to fp32
template <>
inline __host__ __device__ constexpr float type_convert<float, bhalf_t>(bhalf_t x)
{
union
{
uint32_t int32;
float fp32;
} u = {uint32_t(x) << 16};
return u.fp32;
}
// convert fp32 to bfp16
template <>
inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, float>(float x)
{
union
{
float fp32;
uint32_t int32;
} u = {x};
return uint16_t(u.int32 >> 16);
}
// convert bfp16 to fp16 via fp32
template <>
inline __host__ __device__ constexpr half_t type_convert<half_t, bhalf_t>(bhalf_t x)
{
float x_fp32 = type_convert<float>(x);
return static_cast<half_t>(x_fp32);
}
// convert fp16 to bfp16 via fp32
template <>
inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, half_t>(half_t x)
{
float x_fp32 = static_cast<float>(x);
return type_convert<bhalf_t>(x_fp32);
}
// convert bfp16 to int32 via fp32
template <>
inline __host__ __device__ constexpr int32_t type_convert<int32_t, bhalf_t>(bhalf_t x)
{
float x_fp32 = type_convert<float>(x);
return static_cast<int32_t>(x_fp32);
}
// convert int32 to bfp16 via fp32
template <>
inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, int32_t>(int32_t x)
{
float x_fp32 = static_cast<float>(x);
return type_convert<bhalf_t>(x_fp32);
}
// convert bfp16 to int8 via fp32
template <>
inline __host__ __device__ constexpr int8_t type_convert<int8_t, bhalf_t>(bhalf_t x)
{
float x_fp32 = type_convert<float>(x);
return static_cast<int8_t>(x_fp32);
}
// convert int8 to bfp16 via fp32
template <>
inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, int8_t>(int8_t x)
{
float x_fp32 = static_cast<float>(x);
return type_convert<bhalf_t>(x_fp32);
}
// convert fp32 to fp8
template <>
inline __host__ __device__ f8_t type_convert<f8_t, float>(float x)
{
constexpr bool negative_zero_nan = true;
constexpr bool clip = true;
constexpr f8_rounding_mode rm = f8_rounding_mode::standard;
constexpr uint32_t rng = 0;
return cast_to_f8<float, negative_zero_nan, clip, (rm == f8_rounding_mode::stochastic)>(x, rng);
}
// convert fp8 to fp32
template <>
inline __host__ __device__ float type_convert<float, f8_t>(f8_t x)
{
constexpr bool negative_zero_nan = true;
return cast_from_f8<float, negative_zero_nan>(x);
}
// convert fp16 to fp8
template <>
inline __host__ __device__ f8_t type_convert<f8_t, half_t>(half_t x)
{
constexpr bool negative_zero_nan = true;
constexpr bool clip = true;
constexpr f8_rounding_mode rm = f8_rounding_mode::standard;
constexpr uint32_t rng = 0;
return cast_to_f8<half_t, negative_zero_nan, clip, (rm == f8_rounding_mode::stochastic)>(x,
rng);
}
// convert fp8 to fp16
template <>
inline __host__ __device__ half_t type_convert<half_t, f8_t>(f8_t x)
{
constexpr bool negative_zero_nan = true;
return cast_from_f8<half_t, negative_zero_nan>(x);
}
// Declare a template function for bf16 conversion using RTN
template <typename Y, typename X>
__host__ __device__ constexpr Y bf16_convert_rtn(X x);
// Convert fp32 to bf16 with RTN if higher precision is needed
template <>
inline __host__ __device__ constexpr bhalf_t bf16_convert_rtn<bhalf_t, float>(float x)
{
union
{
float fp32;
uint32_t int32;
} u = {x};
// When the exponent bits are not all 1s, then the value is zero, normal,
// or subnormal. We round the bfloat16 mantissa up by adding 0x7FFF, plus
// 1 if the least significant bit of the bfloat16 mantissa is 1 (odd).
// This causes the bfloat16's mantissa to be incremented by 1 if the 16
// least significant bits of the float mantissa are greater than 0x8000,
// or if they are equal to 0x8000 and the least significant bit of the
// bfloat16 mantissa is 1 (odd). This causes it to be rounded to even when
// the lower 16 bits are exactly 0x8000. If the bfloat16 mantissa already
// has the value 0x7f, then incrementing it causes it to become 0x00 and
// the exponent is incremented by one, which is the next higher FP value
// to the unrounded bfloat16 value. When the bfloat16 value is subnormal
// with an exponent of 0x00 and a mantissa of 0x7f, it may be rounded up
// to a normal value with an exponent of 0x01 and a mantissa of 0x00.
// When the bfloat16 value has an exponent of 0xFE and a mantissa of 0x7F,
// incrementing it causes it to become an exponent of 0xFF and a mantissa
// of 0x00, which is Inf, the next higher value to the unrounded value.
bool flag0 = ~u.int32 & 0x7f800000;
// When all of the exponent bits are 1, the value is Inf or NaN.
// Inf is indicated by a zero mantissa. NaN is indicated by any nonzero
// mantissa bit. Quiet NaN is indicated by the most significant mantissa
// bit being 1. Signaling NaN is indicated by the most significant
// mantissa bit being 0 but some other bit(s) being 1. If any of the
// lower 16 bits of the mantissa are 1, we set the least significant bit
// of the bfloat16 mantissa, in order to preserve signaling NaN in case
// the bfloat16's mantissa bits are all 0.
bool flag1 = !flag0 && (u.int32 & 0xffff);
u.int32 += flag0 ? 0x7fff + ((u.int32 >> 16) & 1) : 0; // Round to nearest, round to even
u.int32 |= flag1 ? 0x10000 : 0x0; // Preserve signaling NaN
return uint16_t(u.int32 >> 16);
}
// convert fp16 to bfp16 via fp32 with RTN if higher precision is needed
template <>
inline __host__ __device__ constexpr bhalf_t bf16_convert_rtn<bhalf_t, half_t>(half_t x)
{
float x_fp32 = static_cast<float>(x);
return bf16_convert_rtn<bhalf_t>(x_fp32);
}
// Pseudo random number generator
// version for fp32
template <typename T, uint32_t seed_t, std::enable_if_t<std::is_same<float, T>{}, bool> = false>
__host__ __device__ uint32_t prand_generator(index_t id, T val, uint32_t seed = seed_t)
{
uint32_t x = *(reinterpret_cast<uint32_t*>(&val));
uint32_t drop_bits = uint32_t(x) & 0xFFFFu;
drop_bits ^= x >> 16;
drop_bits = ((drop_bits & 31) << 11) | (drop_bits >> 5);
drop_bits *= 0x7000149;
// NOTE: If id is in 64 bit, we are only using lower 32 bit.
// So, it can have an effect of using same id for multiple elements when the id is very
// large!
uint32_t rng = (drop_bits ^ 0x13371337 ^ (id * 229791) ^ seed);
return rng;
}
// version for fp16
template <typename T, uint32_t seed_t, std::enable_if_t<std::is_same<half_t, T>{}, bool> = false>
__host__ __device__ uint32_t prand_generator(index_t id, T val, uint32_t seed = seed_t)
{
uint16_t x = *(reinterpret_cast<uint16_t*>(&val));
uint32_t drop_bits = uint32_t(x) & 0xFFFFu;
drop_bits = ((drop_bits & 31) << 11) | (drop_bits >> 5);
drop_bits *= 0x7000149;
// NOTE: If id is in 64 bit, we are only using lower 32 bit.
// So, it can have an effect of using same id for multiple elements when the id is very
// large!
uint32_t rng = (drop_bits ^ 0x13371337 ^ (id * 229791) ^ seed);
return rng;
}
// return 0 if data is not fp16 or fp32
template <typename T,
uint32_t seed_t,
std::enable_if_t<!(std::is_same<float, T>{} || std::is_same<half_t, T>{}), bool> = false>
__host__ __device__ uint32_t prand_generator(int id, T val, uint32_t seed = seed_t)
{
std::ignore = id;
std::ignore = val;
std::ignore = seed;
return 0;
}
// Declare a template function for fp8 conversion using SR
template <typename Y, typename X>
__host__ __device__ constexpr Y f8_convert_sr(X x);
// convert fp32 to fp8 with stochastic rounding
template <>
inline __host__ __device__ f8_t f8_convert_sr<f8_t, float>(float x)
{
constexpr bool negative_zero_nan = true;
constexpr bool clip = true;
constexpr f8_rounding_mode rm = f8_rounding_mode::stochastic;
constexpr int seed = 42;
// as thread id is not available on host, use 0 for prn generation
uint32_t rng = prand_generator<float, seed>(reinterpret_cast<uintptr_t>(&x), x);
return cast_to_f8<float, negative_zero_nan, clip, (rm == f8_rounding_mode::stochastic)>(x, rng);
}
// convert fp16 to fp8 with stochastic rounding
template <>
inline __host__ __device__ f8_t f8_convert_sr<f8_t, half_t>(half_t x)
{
constexpr bool negative_zero_nan = true;
constexpr bool clip = true;
constexpr f8_rounding_mode rm = f8_rounding_mode::stochastic;
constexpr int seed = 42;
// as thread id is not available on host, use 0 for prn generation
uint32_t rng = prand_generator<half_t, seed>(reinterpret_cast<uintptr_t>(&x), x);
return cast_to_f8<half_t, negative_zero_nan, clip, (rm == f8_rounding_mode::stochastic)>(x,
rng);
}
template <typename T> template <typename T>
struct NumericLimits struct NumericLimits
{ {
......
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck/utility/f8_utils.hpp"
namespace ck {
using bhalf_t = ushort;
using half_t = _Float16;
#ifdef CK_EXPERIMENTAL_BIT_INT_EXTENSION_INT4
using int4_t = _BitInt(4);
#endif
// Convert X to Y
template <typename Y, typename X>
__host__ __device__ constexpr Y type_convert(X x)
{
static_assert(!std::is_reference_v<Y> && !std::is_reference_v<X>);
return static_cast<Y>(x);
}
// convert bfp16 to fp32
template <>
inline __host__ __device__ constexpr float type_convert<float, bhalf_t>(bhalf_t x)
{
union
{
uint32_t int32;
float fp32;
} u = {uint32_t(x) << 16};
return u.fp32;
}
// convert fp32 to bfp16
template <>
inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, float>(float x)
{
union
{
float fp32;
uint32_t int32;
} u = {x};
return uint16_t(u.int32 >> 16);
}
// convert bfp16 to fp16 via fp32
template <>
inline __host__ __device__ constexpr half_t type_convert<half_t, bhalf_t>(bhalf_t x)
{
float x_fp32 = type_convert<float>(x);
return static_cast<half_t>(x_fp32);
}
// convert fp16 to bfp16 via fp32
template <>
inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, half_t>(half_t x)
{
float x_fp32 = static_cast<float>(x);
return type_convert<bhalf_t>(x_fp32);
}
// convert bfp16 to int32 via fp32
template <>
inline __host__ __device__ constexpr int32_t type_convert<int32_t, bhalf_t>(bhalf_t x)
{
float x_fp32 = type_convert<float>(x);
return static_cast<int32_t>(x_fp32);
}
// convert int32 to bfp16 via fp32
template <>
inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, int32_t>(int32_t x)
{
float x_fp32 = static_cast<float>(x);
return type_convert<bhalf_t>(x_fp32);
}
// convert bfp16 to int8 via fp32
template <>
inline __host__ __device__ constexpr int8_t type_convert<int8_t, bhalf_t>(bhalf_t x)
{
float x_fp32 = type_convert<float>(x);
return static_cast<int8_t>(x_fp32);
}
// convert int8 to bfp16 via fp32
template <>
inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, int8_t>(int8_t x)
{
float x_fp32 = static_cast<float>(x);
return type_convert<bhalf_t>(x_fp32);
}
// convert fp32 to fp8
template <>
inline __host__ __device__ f8_t type_convert<f8_t, float>(float x)
{
constexpr bool negative_zero_nan = true;
constexpr bool clip = true;
constexpr f8_rounding_mode rm = f8_rounding_mode::standard;
constexpr uint32_t rng = 0;
return cast_to_f8<float, negative_zero_nan, clip, (rm == f8_rounding_mode::stochastic)>(x, rng);
}
// convert fp8 to fp32
template <>
inline __host__ __device__ float type_convert<float, f8_t>(f8_t x)
{
constexpr bool negative_zero_nan = true;
return cast_from_f8<float, negative_zero_nan>(x);
}
// convert fp16 to fp8
template <>
inline __host__ __device__ f8_t type_convert<f8_t, half_t>(half_t x)
{
constexpr bool negative_zero_nan = true;
constexpr bool clip = true;
constexpr f8_rounding_mode rm = f8_rounding_mode::standard;
constexpr uint32_t rng = 0;
return cast_to_f8<half_t, negative_zero_nan, clip, (rm == f8_rounding_mode::stochastic)>(x,
rng);
}
// convert fp8 to fp16
template <>
inline __host__ __device__ half_t type_convert<half_t, f8_t>(f8_t x)
{
constexpr bool negative_zero_nan = true;
return cast_from_f8<half_t, negative_zero_nan>(x);
}
// Declare a template function for bf16 conversion using RTN
template <typename Y, typename X>
__host__ __device__ constexpr Y bf16_convert_rtn(X x);
// Convert fp32 to bf16 with RTN if higher precision is needed
template <>
inline __host__ __device__ constexpr bhalf_t bf16_convert_rtn<bhalf_t, float>(float x)
{
union
{
float fp32;
uint32_t int32;
} u = {x};
// When the exponent bits are not all 1s, then the value is zero, normal,
// or subnormal. We round the bfloat16 mantissa up by adding 0x7FFF, plus
// 1 if the least significant bit of the bfloat16 mantissa is 1 (odd).
// This causes the bfloat16's mantissa to be incremented by 1 if the 16
// least significant bits of the float mantissa are greater than 0x8000,
// or if they are equal to 0x8000 and the least significant bit of the
// bfloat16 mantissa is 1 (odd). This causes it to be rounded to even when
// the lower 16 bits are exactly 0x8000. If the bfloat16 mantissa already
// has the value 0x7f, then incrementing it causes it to become 0x00 and
// the exponent is incremented by one, which is the next higher FP value
// to the unrounded bfloat16 value. When the bfloat16 value is subnormal
// with an exponent of 0x00 and a mantissa of 0x7f, it may be rounded up
// to a normal value with an exponent of 0x01 and a mantissa of 0x00.
// When the bfloat16 value has an exponent of 0xFE and a mantissa of 0x7F,
// incrementing it causes it to become an exponent of 0xFF and a mantissa
// of 0x00, which is Inf, the next higher value to the unrounded value.
bool flag0 = ~u.int32 & 0x7f800000;
// When all of the exponent bits are 1, the value is Inf or NaN.
// Inf is indicated by a zero mantissa. NaN is indicated by any nonzero
// mantissa bit. Quiet NaN is indicated by the most significant mantissa
// bit being 1. Signaling NaN is indicated by the most significant
// mantissa bit being 0 but some other bit(s) being 1. If any of the
// lower 16 bits of the mantissa are 1, we set the least significant bit
// of the bfloat16 mantissa, in order to preserve signaling NaN in case
// the bfloat16's mantissa bits are all 0.
bool flag1 = !flag0 && (u.int32 & 0xffff);
u.int32 += flag0 ? 0x7fff + ((u.int32 >> 16) & 1) : 0; // Round to nearest, round to even
u.int32 |= flag1 ? 0x10000 : 0x0; // Preserve signaling NaN
return uint16_t(u.int32 >> 16);
}
// convert fp16 to bfp16 via fp32 with RTN if higher precision is needed
template <>
inline __host__ __device__ constexpr bhalf_t bf16_convert_rtn<bhalf_t, half_t>(half_t x)
{
float x_fp32 = static_cast<float>(x);
return bf16_convert_rtn<bhalf_t>(x_fp32);
}
// Pseudo random number generator
// version for fp32
template <typename T, uint32_t seed_t, std::enable_if_t<std::is_same<float, T>{}, bool> = false>
__host__ __device__ uint32_t prand_generator(index_t id, T val, uint32_t seed = seed_t)
{
uint32_t x = *(reinterpret_cast<uint32_t*>(&val));
uint32_t drop_bits = uint32_t(x) & 0xFFFFu;
drop_bits ^= x >> 16;
drop_bits = ((drop_bits & 31) << 11) | (drop_bits >> 5);
drop_bits *= 0x7000149;
// NOTE: If id is in 64 bit, we are only using lower 32 bit.
// So, it can have an effect of using same id for multiple elements when the id is very
// large!
uint32_t rng = (drop_bits ^ 0x13371337 ^ (id * 229791) ^ seed);
return rng;
}
// version for fp16
template <typename T, uint32_t seed_t, std::enable_if_t<std::is_same<half_t, T>{}, bool> = false>
__host__ __device__ uint32_t prand_generator(index_t id, T val, uint32_t seed = seed_t)
{
uint16_t x = *(reinterpret_cast<uint16_t*>(&val));
uint32_t drop_bits = uint32_t(x) & 0xFFFFu;
drop_bits = ((drop_bits & 31) << 11) | (drop_bits >> 5);
drop_bits *= 0x7000149;
// NOTE: If id is in 64 bit, we are only using lower 32 bit.
// So, it can have an effect of using same id for multiple elements when the id is very
// large!
uint32_t rng = (drop_bits ^ 0x13371337 ^ (id * 229791) ^ seed);
return rng;
}
// return 0 if data is not fp16 or fp32
template <typename T,
uint32_t seed_t,
std::enable_if_t<!(std::is_same<float, T>{} || std::is_same<half_t, T>{}), bool> = false>
__host__ __device__ uint32_t prand_generator(int id, T val, uint32_t seed = seed_t)
{
std::ignore = id;
std::ignore = val;
std::ignore = seed;
return 0;
}
// Declare a template function for fp8 conversion using SR
template <typename Y, typename X>
__host__ __device__ constexpr Y f8_convert_sr(X x);
// convert fp32 to fp8 with stochastic rounding
template <>
inline __host__ __device__ f8_t f8_convert_sr<f8_t, float>(float x)
{
constexpr bool negative_zero_nan = true;
constexpr bool clip = true;
constexpr f8_rounding_mode rm = f8_rounding_mode::stochastic;
constexpr int seed = 42;
// as thread id is not available on host, use 0 for prn generation
uint32_t rng = prand_generator<float, seed>(reinterpret_cast<uintptr_t>(&x), x);
return cast_to_f8<float, negative_zero_nan, clip, (rm == f8_rounding_mode::stochastic)>(x, rng);
}
// convert fp16 to fp8 with stochastic rounding
template <>
inline __host__ __device__ f8_t f8_convert_sr<f8_t, half_t>(half_t x)
{
constexpr bool negative_zero_nan = true;
constexpr bool clip = true;
constexpr f8_rounding_mode rm = f8_rounding_mode::stochastic;
constexpr int seed = 42;
// as thread id is not available on host, use 0 for prn generation
uint32_t rng = prand_generator<half_t, seed>(reinterpret_cast<uintptr_t>(&x), x);
return cast_to_f8<half_t, negative_zero_nan, clip, (rm == f8_rounding_mode::stochastic)>(x,
rng);
}
} // namespace ck
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