Skip to content

GitLab

Commit 13d14c66 authored by Brian Pickrell's avatar Brian Pickrell
Browse files

Merge branch 'develop' into dyn_resize_gather

parents f4e7d9d9 d1abf06f
Show whitespace changes
Inline Side-by-side
Showing with 603 additions and 131 deletions
src/targets/gpu/device/targets.hpp.in 0 → 100644
View file @ 13d14c66
/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
#ifndef MIGRAPHX_GUARD_DEVICE_TARGETS_CPP
#define MIGRAPHX_GUARD_DEVICE_TARGETS_CPP
#include <migraphx/gpu/device/config.hpp>
#include <string>
#include <vector>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
namespace device {
#define MIGRAPHX_GPU_TARGETS "@GPU_TARGETS@" // NOLINT
MIGRAPHX_DEVICE_EXPORT
const std::vector<std::string>& get_targets();
MIGRAPHX_DEVICE_EXPORT
std::string get_targets_as_string();
MIGRAPHX_DEVICE_EXPORT
std::string get_device_name();
} // namespace device
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif // MIGRAPHX_GUARD_DEVICE_TARGETS_CPP
src/targets/gpu/driver/compile_op.cpp
View file @ 13d14c66
......@@ -38,10 +38,8 @@ struct compile_op : action<compile_op>
context ctx;
auto inputs = p.parse_shapes(v.at("inputs"));
auto op = gpu::compile_op(v.at("name").to<std::string>(), ctx, inputs, v);
auto [host_time, device_time] = time_op(ctx, op, inputs, p.get(v, "iterations", 100));
std::cout << op << ": " << host_time << "ms";
if(device_time > 0)
std::cout << ", " << device_time << "ms";
auto t = time_op(ctx, op, inputs, p.get(v, "iterations", 100));
std::cout << op << ": " << t << "ms";
std::cout << std::endl;
}
};
......
src/targets/gpu/driver/run_op.cpp
View file @ 13d14c66
......@@ -43,8 +43,8 @@ struct run_op : action<run_op>
auto op = make_op(name);
if(v.contains("fields"))
op.from_value(v.at("fields"));
auto [host_time, device_time] = time_op(ctx, op, inputs, p.get(v, "iterations", 100));
std::cout << op << ": " << host_time << "ms" << std::endl;
auto t = time_op(ctx, op, inputs, p.get(v, "iterations", 100));
std::cout << op << ": " << t << "ms" << std::endl;
}
};
......
src/targets/gpu/fuse_ck.cpp
View file @ 13d14c66
......@@ -22,10 +22,11 @@
* THE SOFTWARE.
*/
#include <migraphx/gpu/fuse_ck.hpp>
#include <migraphx/gpu/gemm_softmax_gemm.hpp>
#include <migraphx/matcher.hpp>
#include <migraphx/pass_manager.hpp>
#include <migraphx/make_op.hpp>
#include <migraphx/register_op.hpp>
#include <migraphx/gpu/device_name.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -55,7 +56,7 @@ struct ck_gemm
{
check_shapes{inputs, *this}.same_ndims();
if(inputs.size() < 2)
MIGRAPHX_THROW("should have at least two inputs.");
MIGRAPHX_THROW(name() + ": should have at least two inputs.");
auto a = inputs[0];
auto b = inputs[1];
for(const auto& input : inputs)
......@@ -65,27 +66,35 @@ struct ck_gemm
return r;
return r.with_type(mods.front()->get_output_shapes().front().type());
}
static bool is_ck_supported_type(shape::type_t t)
{
return contains({shape::half_type, shape::int8_type, shape::int32_type}, t);
}
};
MIGRAPHX_REGISTER_OP(ck_gemm);
namespace {
bool is_ck_supported_type(shape::type_t t)
struct ck_gemm_softmax_gemm : gemm_softmax_gemm
{
return contains({shape::half_type, shape::int8_type, shape::int32_type}, t);
}
std::string name() const { return "gpu::ck_gemm_softmax_gemm"; }
};
MIGRAPHX_REGISTER_OP(ck_gemm_softmax_gemm);
namespace {
MIGRAPHX_PRED_MATCHER(is_ck_gemm, instruction_ref ins)
{
if(ins->name() != "dot" and ins->name() != "quant_dot")
return false;
if(not is_ck_supported_type(ins->get_shape().type()))
if(not ck_gemm::is_ck_supported_type(ins->get_shape().type()))
return false;
auto a = ins->inputs().front()->get_shape();
auto b = ins->inputs().back()->get_shape();
auto m = a.lens()[a.lens().size() - 2];
auto n = b.lens().back();
auto k = a.lens().back();
auto batch_size = std::accumulate(
a.lens().rbegin() + 2, a.lens().rend(), std::size_t{1}, std::multiplies<std::size_t>());
// Integer gemms must be divisible by 4 in ck
if(contains({shape::int8_type, shape::int32_type}, ins->get_shape().type()))
{
......@@ -96,9 +105,17 @@ MIGRAPHX_PRED_MATCHER(is_ck_gemm, instruction_ref ins)
if(k % 4 != 0)
return false;
}
// Skipping GEMMs with a K dimension greater than 2048 is a course-grained strategy
// to avoid poor-performing GEMM kernels from CK
// To-do: Investigate a more precise strategy
auto device_name = trim(split_string(get_device_name(), ':').front());
if(device_name == "gfx940")
{
if(ins->get_shape().type() == shape::half_type)
{
if(batch_size >= 64)
return m < 2048 or k <= 64 or n <= 384 or n >= 2048;
return true;
}
return true;
}
return k <= 2048;
}
......@@ -127,7 +144,15 @@ struct find_ck_gemm_pointwise
ins->get_shape().type() != gemm_ins->get_shape().type())
return;
if(std::any_of(ins->inputs().begin(), ins->inputs().end(), [](auto input) {
return not is_ck_supported_type(input->get_shape().type());
return not ck_gemm::is_ck_supported_type(input->get_shape().type());
}))
return;
if(std::any_of(ins->inputs().begin(), ins->inputs().end(), [](auto input) {
return not input->inputs().empty() and input->inputs().front()->name() == "capture";
}))
return;
if(std::any_of(ins->inputs().begin(), ins->inputs().end(), [](auto input) {
return not input->inputs().empty() and input->inputs().front()->name() == "capture";
}))
return;
assert(gemm_it != inputs.end());
......@@ -152,7 +177,7 @@ struct find_ck_gemm_pointwise
struct find_ck_gemm
{
auto matcher() const { return match::name("dot")(is_ck_gemm().bind("gemm")); }
auto matcher() const { return match::name("dot", "quant_dot")(is_ck_gemm().bind("gemm")); }
void apply(module_pass_manager& mpm, const match::matcher_result& r) const
{
......@@ -161,11 +186,26 @@ struct find_ck_gemm
}
};
struct find_ck_gemm_softmax_gemm
{
auto matcher() const { return match::name("gpu::pre_gemm_softmax_gemm"); }
void apply(module_pass_manager& mpm, const match::matcher_result& r) const
{
auto ins = r.result;
auto v = ins->get_operator().to_value();
assert(v.contains("scale"));
auto scale = v.at("scale").to<float>();
mpm.get_module().replace_instruction(
ins, ck_gemm_softmax_gemm{migraphx::make_op("dot"), scale}, ins->inputs());
}
};
} // namespace
void fuse_ck::apply(module_pass_manager& mpm) const
{
match::find_matches(mpm, find_ck_gemm_pointwise{});
match::find_matches(mpm, find_ck_gemm_softmax_gemm{}, find_ck_gemm_pointwise{});
match::find_matches(mpm, find_ck_gemm{});
}
......
src/targets/gpu/fuse_mlir.cpp
View file @ 13d14c66
......@@ -36,24 +36,14 @@ struct module;
namespace gpu {
MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_ENABLE_MLIR);
MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_ENABLE_EXTRA_MLIR);
MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_DISABLE_MLIR);
bool mlir_enabled()
{
#ifdef MIGRAPHX_MLIR
const bool mlir_enabled = enabled(MIGRAPHX_ENABLE_MLIR{});
if(mlir_enabled)
{
return true;
}
else
{
std::cerr << "WARNING: MIGraphX built with MLIR but it is not enabled. Please set the env "
"var MIGRAPHX_ENABLE_MLIR to use MLIR kernel generator."
<< std::endl;
return false;
}
const bool mlir_disabled = enabled(MIGRAPHX_DISABLE_MLIR{});
return not mlir_disabled;
#else
return false;
#endif
......@@ -103,7 +93,10 @@ struct mlir_op
}
if(ins->name() == "@return")
{
return ins_shapes[ins->inputs().at(0)].with_type(type);
auto s = ins_shapes[ins->inputs().at(0)].with_type(type);
if(not s.standard())
MIGRAPHX_THROW("MLIR doesnt support non-standard output");
return s;
}
std::vector<shape> input_shapes;
input_shapes.resize(ins->inputs().size());
......@@ -119,9 +112,75 @@ struct mlir_op
MIGRAPHX_REGISTER_OP(mlir_op);
namespace {
std::tuple<instruction_ref, std::vector<instruction_ref>>
fuse_input_ops_and_gemm_based_op(module_ref mm, instruction_ref gemm_based_op)
{
std::vector<instruction_ref> top_inputs;
std::vector<instruction_ref> imm_inputs;
size_t input_cnt = 0;
for(instruction_ref input : gemm_based_op->inputs())
{
std::vector<operation> op_stream;
while(contains(
{"slice", "transpose", "contiguous", "reshape", "squeeze", "flatten", "unsqueeze"},
input->name()))
{
operation op = input->get_operator();
if(contains({"squeeze", "flatten", "unsqueeze"}, input->name()))
{
op = migraphx::make_op("reshape", {{"dims", input->get_shape().lens()}});
}
op_stream.push_back(op);
input = input->inputs().at(0);
}
top_inputs.push_back(input);
instruction_ref prev_input =
mm->add_parameter("y" + std::to_string(input_cnt++), input->get_shape());
for(const auto& op : reverse(op_stream))
{
prev_input = mm->add_instruction(op, {prev_input});
}
imm_inputs.push_back(prev_input);
}
instruction_ref new_gemm_based_op =
mm->add_instruction(gemm_based_op->get_operator(), imm_inputs);
return {new_gemm_based_op, top_inputs};
}
enum class mlir_mode
{
all,
fast,
int8,
none
};
auto is_mlir_dot(mlir_mode mode)
{
return match::make_basic_pred_matcher([=](instruction_ref ins) {
if(mode == mlir_mode::none)
return false;
if(ins->name() != "dot" and ins->name() != "quant_dot")
return false;
if(mode != mlir_mode::fast)
return true;
auto a = ins->inputs().front()->get_shape();
auto b = ins->inputs().back()->get_shape();
// auto m = a.lens()[a.lens().size() - 2];
// auto n = b.lens().back();
auto k = a.lens().back();
// Skipping GEMMs with a K dimension greater than 2048 is a course-grained strategy
// to avoid poor-performing GEMM kernels from MLIR
// To-do: Investigate a more precise strategy
return k <= 2048;
});
}
MIGRAPHX_PRED_MATCHER(is_mlir_conv, instruction_ref ins)
auto is_mlir_conv(mlir_mode mode)
{
return match::make_basic_pred_matcher([=](instruction_ref ins) {
if(mode == mlir_mode::none)
return false;
if(ins->name() != "convolution" and ins->name() != "quant_convolution")
return false;
value v = ins->get_operator().to_value();
......@@ -131,16 +190,29 @@ MIGRAPHX_PRED_MATCHER(is_mlir_conv, instruction_ref ins)
// Avoid MLIR assertion: Index < Length && "Invalid index!"
if(ins->get_shape().lens().size() != 4)
return false;
if(ins->get_shape().type() == shape::int8_type)
return true;
if(mode == mlir_mode::int8)
return false;
if(mode == mlir_mode::all)
return true;
auto w = ins->inputs().at(1)->get_shape();
if(w.lens().size() != 4)
return true;
if(w.lens()[2] != w.lens()[3])
return true;
return (w.lens()[3] % 3) != 0;
});
}
struct find_mlir_op
struct find_mlir_fused_ops
{
mlir_mode conv_mode = mlir_mode::none;
mlir_mode dot_mode = mlir_mode::none;
auto matcher() const
{
auto dot_or_conv = match::skip(match::name("contiguous"))(
match::any_of(match::name("dot"), match::name("quant_dot"), is_mlir_conv())
.bind("gemm_based_op"));
match::any_of(is_mlir_dot(dot_mode), is_mlir_conv(conv_mode)).bind("gemm_based_op"));
return match::name("pointwise")(match::any_of[match::inputs()](dot_or_conv.bind("x")));
}
......@@ -163,34 +235,6 @@ struct find_mlir_op
return ins_map;
}
std::tuple<instruction_ref, std::vector<instruction_ref>>
fuse_input_ops_and_gemm_based_op(module_ref mm, instruction_ref gemm_based_op) const
{
std::vector<instruction_ref> top_inputs;
std::vector<instruction_ref> imm_inputs;
size_t input_cnt = 0;
for(instruction_ref input : gemm_based_op->inputs())
{
std::vector<operation> op_stream;
while(contains({"slice", "transpose", "contiguous", "reshape"}, input->name()))
{
op_stream.push_back(input->get_operator());
input = input->inputs().at(0);
}
top_inputs.push_back(input);
instruction_ref prev_input =
mm->add_parameter("y" + std::to_string(input_cnt++), input->get_shape());
for(const auto& op : reverse(op_stream))
{
prev_input = mm->add_instruction(op, {prev_input});
}
imm_inputs.push_back(prev_input);
}
instruction_ref new_gemm_based_op =
mm->add_instruction(gemm_based_op->get_operator(), imm_inputs);
return {new_gemm_based_op, top_inputs};
}
// Whitelist supported fusion options, including imposing type constraints
// for cases where MLIR only supports an operation (usually a pointwise function)
// on particular types.
......@@ -236,8 +280,7 @@ struct find_mlir_op
"log",
"recip",
"rsqrt",
// There are bugs in MLIR right now for models using sigmoid so disable it for now
// "sigmoid",
"sigmoid",
"softmax",
"tanh",
};
......@@ -282,9 +325,9 @@ struct find_mlir_op
names.end(),
ins->inputs().begin(),
std::inserter(param_map, param_map.end()),
[&, &anchor_op = anchor_op](auto name, auto input) {
[&, &anchor = anchor_op](auto name, auto input) {
if(input == x_ins)
return std::make_pair(pm->get_parameter(name), anchor_op);
return std::make_pair(pm->get_parameter(name), anchor);
return std::make_pair(pm->get_parameter(name),
mm->add_parameter(name, input->get_shape()));
});
......@@ -301,20 +344,91 @@ struct find_mlir_op
}
};
template <auto Matcher>
struct find_mlir_standalone_op
{
mlir_mode mode = mlir_mode::none;
auto matcher() const { return Matcher(mode); }
void apply(module_pass_manager& mpm, const match::matcher_result& r) const
{
auto conv_based_op = r.result;
// enable only for fp32/fp16/i8 types
if(std::any_of(conv_based_op->inputs().begin(), conv_based_op->inputs().end(), [&](auto i) {
return not contains(
{shape::type_t::float_type, shape::type_t::half_type, shape::type_t::int8_type},
i->get_shape().type());
}))
return;
static size_t counter = 0;
module_ref mm =
mpm.create_module("mlir_" + conv_based_op->name() + std::to_string(counter++));
mm->set_bypass();
auto [anchor_op, top_inputs] = fuse_input_ops_and_gemm_based_op(mm, conv_based_op);
mm->add_return({anchor_op});
mpm.get_module().replace_instruction(
conv_based_op, mlir_op{conv_based_op->get_operator()}, top_inputs, {mm});
}
};
using find_mlir_standalone_convolution_op = find_mlir_standalone_op<&is_mlir_conv>;
using find_mlir_standalone_dot_op = find_mlir_standalone_op<&is_mlir_dot>;
/**
* @brief Declares a new MIGraphX environment variable which forces to generate
* only specific MLIR operations.
*
* The variable, if defined, forces MIGraphX to use only specific operations
* with MLIR regardless of the underlying GPU architecture. The variable accepts
* a list of operations separated by comma. The variable recognizes the following
* operations: "fused", "convolution", "dot". If the variable is not defined MIGraphX
* will decide by itself which operations to delegate to MLIR. The variable is
* intended to be primarily used by rocMLIR developers.
*/
MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_MLIR_USE_SPECIFIC_OPS);
bool is_requested(std::string_view option, bool fallback = false)
{
auto string_value = string_value_of(MIGRAPHX_MLIR_USE_SPECIFIC_OPS{}, "");
if(string_value.empty())
return fallback;
const auto options = split_string(string_value, ',');
return contains(options, option);
}
} // namespace
#endif
#endif // MIGRAPHX_MLIR
void fuse_mlir::apply(module_pass_manager& mpm) const
{
#ifdef MIGRAPHX_MLIR
match::find_matches(mpm, find_mlir_op{});
const auto& device_name = ctx == nullptr ? "" : ctx->get_current_device().get_gfx_name();
const bool is_navi = starts_with(device_name, "gfx110");
auto get_mode = [&](std::string_view option, mlir_mode m1, mlir_mode m2 = mlir_mode::fast) {
if(is_requested(option))
return mlir_mode::all;
if(is_navi)
return mlir_mode::all;
return std::max(m1, m2);
};
mlir_mode mode =
(enabled(MIGRAPHX_ENABLE_EXTRA_MLIR{}) or enable_extra) ? mlir_mode::fast : mlir_mode::none;
match::find_matches(mpm,
find_mlir_fused_ops{.conv_mode = get_mode("fused", mlir_mode::fast),
.dot_mode = get_mode("fused", mode)});
match::find_matches(
mpm,
find_mlir_standalone_convolution_op{get_mode("convolution", mlir_mode::int8)},
find_mlir_standalone_dot_op{get_mode("dot", mlir_mode::none)});
#else
(void)mpm;
#endif
}
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
src/targets/gpu/fuse_ops.cpp
View file @ 13d14c66
......@@ -790,22 +790,26 @@ struct find_layernorm_pointwise
{
auto matcher() const
{
return precompile_name("pointwise")(match::arg(0)(
return precompile_name("pointwise")(match::any_of[match::inputs()](
precompile_name("gpu::prelayernorm", "gpu::preadd_layernorm").bind("layernorm")));
}
void apply(module& m, const match::matcher_result& r) const
{
auto ins = r.result;
auto pw_ins = r.result;
auto layernorm = r.instructions["layernorm"];
if(not layernorm->module_inputs().empty())
return;
auto* pm = ins->module_inputs().front();
auto* pm = pw_ins->module_inputs().front();
auto pw_inputs = pw_ins->inputs();
auto ln_pos = std::find(pw_inputs.begin(), pw_inputs.end(), layernorm);
assert(ln_pos != pw_inputs.end());
pw_inputs.erase(ln_pos);
auto inputs = layernorm->inputs();
inputs.pop_back();
inputs.insert(inputs.end(), ins->inputs().begin() + 1, ins->inputs().end());
inputs.insert(inputs.end(), pw_inputs.begin(), pw_inputs.end());
m.replace_instruction(ins, layernorm->get_operator(), inputs, {pm});
m.replace_instruction(pw_ins, layernorm->get_operator(), inputs, {pm});
}
};
......
src/targets/gpu/hiprtc/main.cpp
View file @ 13d14c66
......@@ -27,6 +27,7 @@
#include <migraphx/msgpack.hpp>
#include <migraphx/file_buffer.hpp>
#include <migraphx/ranges.hpp>
#include <array>
#include <iostream>
#include <cstring>
......
src/targets/gpu/include/migraphx/gpu/ck.hpp 0 → 100644
View file @ 13d14c66
/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
#ifndef MIGRAPHX_GUARD_GPU_CK_HPP
#define MIGRAPHX_GUARD_GPU_CK_HPP
#include <migraphx/compile_src.hpp>
#include <migraphx/env.hpp>
#include <migraphx/shape.hpp>
#include <migraphx/stringutils.hpp>
#include <string_view>
#include "ck/host/device_gemm_multiple_d.hpp"
#include "ck/host/device_batched_gemm_softmax_gemm.hpp"
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
#ifndef _WIN32
MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_ENABLE_CK);
MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_LOG_CK_GEMM);
MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_CK_DEBUG);
MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_TUNE_CK);
#endif
// NOLINTNEXTLINE
const char* const disable_warning_pragma = R"__migraphx__(
#pragma clang diagnostic push
#pragma clang diagnostic ignored "-Weverything"
${content}
#pragma clang diagnostic pop
)__migraphx__";
template <class P>
std::string ck_disable_warnings(P p)
{
return interpolate_string(disable_warning_pragma,
{{"content", std::string{p.data(), p.size()}}});
}
static std::unordered_map<std::string, std::string> create_ck_header_strings()
{
std::unordered_map<std::string, std::string> result;
auto ck_headers = ck::host::GetHeaders();
std::transform(
ck_headers.begin(), ck_headers.end(), std::inserter(result, result.begin()), [&](auto& p) {
return std::pair<std::string, std::string>(p.first, ck_disable_warnings(p.second));
});
return result;
}
static std::vector<src_file> create_ck_headers()
{
static const auto& header_strings = create_ck_header_strings();
std::vector<src_file> srcs;
std::transform(header_strings.begin(),
header_strings.end(),
std::back_inserter(srcs),
[&](auto& p) { return src_file{p}; });
return srcs;
}
static inline const std::vector<src_file>& ck_headers()
{
static const auto& headers = create_ck_headers();
return headers;
}
inline bool transposed_matrix(const shape& s) { return s.strides().back() != 1; }
inline ck::host::DataType get_type(const shape& s)
{
if(s.type() == shape::half_type)
return ck::host::DataType::Half;
else if(s.type() == shape::float_type)
return ck::host::DataType::Float;
else if(s.type() == shape::int8_type)
return ck::host::DataType::Int8;
else if(s.type() == shape::int32_type)
return ck::host::DataType::Int32;
MIGRAPHX_THROW("Unsupported ck type");
}
inline std::size_t get_batch_count(const shape& s)
{
return std::accumulate(
s.lens().rbegin() + 2, s.lens().rend(), std::size_t{1}, std::multiplies<std::size_t>());
}
inline void fold_batch_dims(shape& s)
{
auto lens = s.lens();
if(lens.size() <= 2)
return;
auto batch_count = get_batch_count(s);
auto m1 = lens.at(lens.size() - 2);
auto m2 = lens.at(lens.size() - 1);
if(transposed_matrix(s))
s = shape{s.type(), {m1, m2 * batch_count}};
else
s = shape{s.type(), {m1 * batch_count, m2}};
}
inline void remove_batch_dims(shape& s)
{
auto lens = s.lens();
if(lens.size() <= 2)
return;
auto m1 = lens.at(lens.size() - 2);
auto m2 = lens.at(lens.size() - 1);
s = shape{s.type(), {m1, m2}};
}
inline bool standard_batch(const shape& s)
{
if(s.lens().size() < 3)
return true;
std::vector<std::size_t> lens(s.lens().begin(), s.lens().end() - 2);
std::vector<std::size_t> strides(s.strides().begin(), s.strides().end() - 2);
auto base = *(s.lens().end() - 2) * *(s.lens().end() - 1);
std::transform(strides.begin(), strides.end(), strides.begin(), [&](auto stride) {
return stride / base;
});
return shape{s.type(), lens, strides}.standard();
}
inline bool can_fold_batch(const std::vector<shape>& inputs)
{
const auto& b_shape = inputs[1];
if(std::any_of(inputs.begin() + 2, inputs.end() - 1, [](auto input) {
return not standard_batch(input);
}))
return false;
const auto& b_strides = b_shape.strides();
return std::all_of(
b_strides.begin(), b_strides.end() - 2, [](auto stride) { return stride == 0; });
}
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif // MIGRAPHX_GUARD_GPU_CK_HPP
src/targets/gpu/include/migraphx/gpu/compile_hip.hpp
View file @ 13d14c66
......@@ -45,10 +45,7 @@ MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_ENABLE_HIPRTC_WORKAROUNDS);
struct hiprtc_src_file
{
hiprtc_src_file() = default;
hiprtc_src_file(const src_file& s)
: path(s.path.string()), content(s.content.first, s.content.second)
{
}
hiprtc_src_file(const src_file& s) : path(s.path.string()), content(s.content) {}
std::string path;
std::string content;
template <class Self, class F>
......@@ -58,6 +55,8 @@ struct hiprtc_src_file
}
};
MIGRAPHX_GPU_EXPORT bool hip_has_flags(const std::vector<std::string>& flags);
MIGRAPHX_GPU_EXPORT std::vector<std::vector<char>> compile_hip_src_with_hiprtc(
std::vector<hiprtc_src_file> srcs, std::string params, const std::string& arch);
......
src/targets/gpu/include/migraphx/gpu/context.hpp
View file @ 13d14c66
......@@ -299,23 +299,6 @@ struct context
any_ptr get_queue() { return get_stream().get(); }
void enable_perf_measurement(bool b = true)
{
if(b)
{
start_event = create_event_for_timing();
stop_event = create_event_for_timing();
get_stream().record(start_event.get());
get_stream().record(stop_event.get());
}
else
{
start_event = nullptr;
stop_event = nullptr;
}
measure_perf = b;
}
std::pair<hipEvent_t, hipEvent_t> get_perf_events() const
{
if(measure_perf)
......@@ -323,12 +306,12 @@ struct context
return std::make_pair(nullptr, nullptr);
}
float get_elapsed_ms() const
static float get_elapsed_ms(hipEvent_t start, hipEvent_t stop)
{
float result = 0;
if(start_event != nullptr and stop_event != nullptr)
if(start != nullptr and stop != nullptr)
{
auto status = hipEventElapsedTime(&result, start_event.get(), stop_event.get());
auto status = hipEventElapsedTime(&result, start, stop);
if(status != hipSuccess)
MIGRAPHX_THROW("Failed hipEventElapsedTime: " + hip_error(status));
}
......
src/targets/gpu/include/migraphx/gpu/convolution.hpp
View file @ 13d14c66
......@@ -84,8 +84,10 @@ struct miopen_convolution
{
check_shapes{inputs, op}.has(4);
std::vector<shape> conv_inputs(inputs.begin(), inputs.begin() + 2);
check_shapes{conv_inputs, *this}.max_ndims(5).packed_layouts(
{{0, 1, 2}, {0, 1, 2, 3}, {0, 2, 3, 1}, {0, 1, 2, 3, 4}});
check_shapes{conv_inputs, *this}
.max_ndims(5)
.packed_layouts({{0, 1, 2}, {0, 1, 2, 3}, {0, 2, 3, 1}, {0, 1, 2, 3, 4}})
.same_layout();
return migraphx::compute_shape<Op>(op, conv_inputs);
}
......@@ -197,9 +199,9 @@ struct miopen_convolution
// MIOpen has APIs to pass pre-allocated buffers starting from rocm-5.6
preallocate = true;
#endif
auto x = preallocate ? to_gpu(generate_argument(x_shape)) : inputs[0];
auto w = preallocate ? to_gpu(generate_argument(w_shape)) : inputs[1];
auto y = preallocate ? allocate_gpu(output_shape) : inputs[2];
auto x = preallocate ? to_gpu(generate_argument(x_shape)) : argument{inputs[0]};
auto w = preallocate ? to_gpu(generate_argument(w_shape)) : argument{inputs[1]};
auto y = preallocate ? allocate_gpu(output_shape) : argument{inputs[2]};
auto workspace =
preallocate ? allocate_gpu(workspace_shape) : migraphx::argument(workspace_shape);
......
src/targets/gpu/include/migraphx/gpu/device/arg_op.hpp
View file @ 13d14c66
/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
* Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
......@@ -55,7 +55,7 @@ MIGRAPHX_DEVICE_CONSTEXPR val_index<T> make_val_index(T v, int64_t i)
return {v, i};
}
struct argmax_op
struct argmax_op_first_index
{
template <class T>
MIGRAPHX_DEVICE_CONSTEXPR val_index<T> operator()(val_index<T> x, val_index<T> y) const
......@@ -73,7 +73,25 @@ struct argmax_op
MIGRAPHX_DEVICE_CONSTEXPR auto init() const { return lowest(); }
};
struct argmin_op
struct argmax_op_last_index
{
template <class T>
MIGRAPHX_DEVICE_CONSTEXPR val_index<T> operator()(val_index<T> x, val_index<T> y) const
{
if(x.val > y.val)
return x;
else if(x.val < y.val)
return y;
else
{
return (x.index > y.index) ? x : y;
}
}
MIGRAPHX_DEVICE_CONSTEXPR auto init() const { return lowest(); }
};
struct argmin_op_first_index
{
template <class T>
MIGRAPHX_DEVICE_CONSTEXPR val_index<T> operator()(val_index<T> x, val_index<T> y) const
......@@ -91,6 +109,24 @@ struct argmin_op
MIGRAPHX_DEVICE_CONSTEXPR auto init() const { return highest(); }
};
struct argmin_op_last_index
{
template <class T>
MIGRAPHX_DEVICE_CONSTEXPR val_index<T> operator()(val_index<T> x, val_index<T> y) const
{
if(x.val < y.val)
return x;
else if(x.val > y.val)
return y;
else
{
return (x.index > y.index) ? x : y;
}
}
MIGRAPHX_DEVICE_CONSTEXPR auto init() const { return highest(); }
};
template <class Op>
void arg_op(Op op, hipStream_t stream, const argument& result, const argument& arg, int64_t axis)
{
......
src/targets/gpu/include/migraphx/gpu/device/argmax.hpp
View file @ 13d14c66
/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
* Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
......@@ -36,7 +36,8 @@ namespace device {
void MIGRAPHX_DEVICE_EXPORT argmax(hipStream_t stream,
const argument& result,
const argument& arg,
int64_t axis);
int64_t axis,
bool select_last_index);
} // namespace device
} // namespace gpu
......
src/targets/gpu/include/migraphx/gpu/device/argmin.hpp
View file @ 13d14c66
/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
* Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
......@@ -36,7 +36,8 @@ namespace device {
void MIGRAPHX_DEVICE_EXPORT argmin(hipStream_t stream,
const argument& result,
const argument& arg,
int64_t axis);
int64_t axis,
bool select_last_index);
} // namespace device
} // namespace gpu
......
src/targets/gpu/include/migraphx/gpu/fuse_mlir.hpp
View file @ 13d14c66
......@@ -38,6 +38,7 @@ MIGRAPHX_GPU_EXPORT bool mlir_enabled();
struct MIGRAPHX_GPU_EXPORT fuse_mlir
{
context* ctx = nullptr;
bool enable_extra = false;
std::string name() const { return "gpu::fuse_mlir"; }
void apply(module_pass_manager& mpm) const;
};
......
src/targets/gpu/include/migraphx/gpu/fuse_ops.hpp
View file @ 13d14c66
......@@ -24,7 +24,6 @@
#ifndef MIGRAPHX_GUARD_RTGLIB_FUSE_OPS_HPP
#define MIGRAPHX_GUARD_RTGLIB_FUSE_OPS_HPP
#include <migraphx/config.hpp>
#include <migraphx/gpu/context.hpp>
namespace migraphx {
......@@ -34,7 +33,7 @@ struct module;
namespace gpu {
struct fuse_ops
struct MIGRAPHX_GPU_EXPORT fuse_ops
{
context* ctx = nullptr;
bool fast_math = true;
......
src/targets/gpu/include/migraphx/gpu/gemm_softmax_gemm.hpp 0 → 100644
View file @ 13d14c66
/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
#ifndef MIGRAPHX_GUARD_GPU_GEMM_SOFTMAX_GEMM_HPP
#define MIGRAPHX_GUARD_GPU_GEMM_SOFTMAX_GEMM_HPP
#include <migraphx/make_op.hpp>
#include <migraphx/check_shapes.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
struct gemm_softmax_gemm
{
operation op = make_op("dot");
float scale = 1.0;
template <class Self, class F>
static auto reflect(Self& self, F f)
{
return pack(f(self.op, "op"), f(self.scale, "scale"));
}
std::string name() const { return "gpu::gemm_softmax_gemm"; }
void check_gemm_shape(const shape& s) const
{
if(not contains(range(s.strides().rbegin(), s.strides().rbegin() + 3), 1))
MIGRAPHX_THROW("Invalid shape for " + name());
}
shape compute_shape(std::vector<shape> inputs, const std::vector<module_ref>&) const
{
check_shapes{inputs, *this}.same_ndims();
if(inputs.size() < 3)
MIGRAPHX_THROW(name() + ": Expected 3 inputs but got " + to_string(inputs.size()));
auto a = inputs[0];
auto b = inputs[1];
auto b1 = inputs[2];
for(const auto& input : inputs)
{
check_gemm_shape(input);
}
return op.compute_shape({op.compute_shape({a, b}), b1});
}
static bool is_ck_supported_type(shape::type_t t) { return contains({shape::half_type}, t); }
};
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif // MIGRAPHX_GUARD_GPU_GEMM_SOFTMAX_GEMM_HPP
src/targets/gpu/include/migraphx/gpu/mlir.hpp
View file @ 13d14c66
......@@ -49,7 +49,8 @@ MIGRAPHX_GPU_EXPORT instruction_ref insert_mlir(module& m,
MIGRAPHX_GPU_EXPORT tuning_config get_tuning_config_mlir(const context& migraphx_ctx,
module m,
const std::vector<shape>& inputs);
const std::vector<shape>& inputs,
bool exhaustive);
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
......
src/targets/gpu/include/migraphx/gpu/prefuse_ops.hpp
View file @ 13d14c66
......@@ -24,7 +24,7 @@
#ifndef MIGRAPHX_GUARD_GPU_PREFUSE_OPS_HPP
#define MIGRAPHX_GUARD_GPU_PREFUSE_OPS_HPP
#include <migraphx/config.hpp>
#include <migraphx/gpu/config.hpp>
#include <string>
namespace migraphx {
......@@ -34,7 +34,7 @@ struct module_pass_manager;
namespace gpu {
struct prefuse_ops
struct MIGRAPHX_GPU_EXPORT prefuse_ops
{
std::string name() const { return "gpu::prefuse_ops"; }
void apply(module_pass_manager& mpm) const;
......
src/targets/gpu/include/migraphx/gpu/time_op.hpp
View file @ 13d14c66
......@@ -32,7 +32,7 @@ namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
MIGRAPHX_GPU_EXPORT std::pair<double, double>
MIGRAPHX_GPU_EXPORT double
time_op(context& ictx, operation op, const std::vector<shape>& inputs, int n = 100);
} // namespace gpu
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment