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Commit 77190058 authored by Alan Turner's avatar Alan Turner
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Formatting

parent 421734ae
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Showing with 366 additions and 330 deletions
include/ck/tensor_operation/gpu/grid/block_to_ctile_map.hpp
View file @ 77190058
......@@ -120,22 +120,24 @@ struct BlockToCTileMap_M00_N0_M01Adapt<MPerBlock, NPerBlock, void>
__host__ __device__ constexpr BlockToCTileMap_M00_N0_M01Adapt() = default;
__host__ __device__ constexpr BlockToCTileMap_M00_N0_M01Adapt(const BlockToCTileMap_M00_N0_M01Adapt&) =
default;
__host__ __device__ constexpr BlockToCTileMap_M00_N0_M01Adapt(BlockToCTileMap_M00_N0_M01Adapt&&) =
default;
__host__ __device__ constexpr BlockToCTileMap_M00_N0_M01Adapt(
const BlockToCTileMap_M00_N0_M01Adapt&) = default;
__host__ __device__ constexpr BlockToCTileMap_M00_N0_M01Adapt(
BlockToCTileMap_M00_N0_M01Adapt&&) = default;
__host__ __device__ constexpr BlockToCTileMap_M00_N0_M01Adapt&
operator=(const BlockToCTileMap_M00_N0_M01Adapt&) = default;
__host__ __device__ constexpr BlockToCTileMap_M00_N0_M01Adapt&
operator=(BlockToCTileMap_M00_N0_M01Adapt&&) = default;
__host__ __device__ constexpr BlockToCTileMap_M00_N0_M01Adapt(index_t M, index_t N, index_t M01 = 8)
__host__
__device__ constexpr BlockToCTileMap_M00_N0_M01Adapt(index_t M, index_t N, index_t M01 = 8)
: M_(M), N_(N), M01_(M01)
{
}
template <typename CGridDesc_M_N>
__host__ __device__ constexpr BlockToCTileMap_M00_N0_M01Adapt(const CGridDesc_M_N& c_grid_desc_m_n,
__host__
__device__ constexpr BlockToCTileMap_M00_N0_M01Adapt(const CGridDesc_M_N& c_grid_desc_m_n,
index_t M01 = 8)
: BlockToCTileMap_M00_N0_M01Adapt(
c_grid_desc_m_n.GetLength(I0), c_grid_desc_m_n.GetLength(I1), M01)
......@@ -151,13 +153,15 @@ struct BlockToCTileMap_M00_N0_M01Adapt<MPerBlock, NPerBlock, void>
}
template <typename CGridDesc_M_N>
__host__ __device__ static constexpr index_t CalculateGridSize(const CGridDesc_M_N& c_grid_desc_m_n)
__host__ __device__ static constexpr index_t
CalculateGridSize(const CGridDesc_M_N& c_grid_desc_m_n)
{
return CalculateGridSize(c_grid_desc_m_n.GetLength(I0), c_grid_desc_m_n.GetLength(I1));
}
template <typename CGridDesc_M_N>
__host__ __device__ constexpr bool CheckValidity(const CGridDesc_M_N& /* c_grid_desc_m_n */) const
__host__ __device__ constexpr bool
CheckValidity(const CGridDesc_M_N& /* c_grid_desc_m_n */) const
{
return true;
}
......
library/src/jit_library/include/ck/host/common.hpp
View file @ 77190058
......@@ -17,7 +17,8 @@ struct Solution
std::size_t grid_size;
};
enum class DataType {
enum class DataType
{
Half,
Float,
Int8,
......@@ -26,7 +27,7 @@ enum class DataType {
std::string ToString(DataType dt);
std::unordered_map<std::string, std::pair<const char*,const char*>> GetHeaders();
std::unordered_map<std::string, std::pair<const char*, const char*>> GetHeaders();
std::size_t integer_divide_ceil(std::size_t x, std::size_t y);
......
library/src/jit_library/include/ck/host/device_gemm_multiple_d.hpp
View file @ 77190058
......@@ -11,7 +11,6 @@
#include <numeric>
#include "ck/host/common.hpp"
namespace ck {
namespace host {
namespace device_gemm_multiple_d {
......@@ -49,7 +48,7 @@ struct Problem
std::vector<Solution> GetSolutions(const std::string& arch) const;
private:
private:
std::vector<std::string> GetInstances(const std::string& arch) const;
Solution MakeSolution(std::size_t idx, const std::string& arch) const;
......
library/src/jit_library/src/common.cpp
View file @ 77190058
......@@ -8,7 +8,8 @@ namespace host {
std::string ToString(DataType dt)
{
switch (dt) {
switch(dt)
{
case DataType::Float: return "float";
case DataType::Half: return "ck::half_t";
case DataType::Int8: return "int8_t";
......@@ -17,7 +18,7 @@ std::string ToString(DataType dt)
throw std::runtime_error("Incorrect data type");
}
std::unordered_map<std::string, std::pair<const char*,const char*>> GetHeaders()
std::unordered_map<std::string, std::pair<const char*, const char*>> GetHeaders()
{
return ck_headers();
}
......
library/src/jit_library/src/device_gemm_multiple_d.cpp
View file @ 77190058
......@@ -33,8 +33,7 @@ std::size_t GetGridSize(const std::size_t m,
const std::size_t m_per_block,
const std::size_t n_per_block)
{
return integer_divide_ceil(m, m_per_block) *
integer_divide_ceil(n, n_per_block);
return integer_divide_ceil(m, m_per_block) * integer_divide_ceil(n, n_per_block);
}
const std::unordered_set<std::string>& get_xdlop_archs()
......@@ -47,7 +46,7 @@ std::vector<std::string> Problem::GetInstances(const std::string& arch) const
{
std::vector<std::string> instances;
const bool quantize = ADataType == DataType::Int8 and BDataType == DataType::Int8;
if (get_xdlop_archs().find(arch) != get_xdlop_archs().end())
if(get_xdlop_archs().find(arch) != get_xdlop_archs().end())
{
ck::host::instance::gemm_add_add_fastgelu_instances all_instances{};
if(TransA and TransB)
......@@ -68,9 +67,10 @@ std::string MakeLayoutTuple(const std::vector<bool>& layouts)
auto it = layouts.begin();
while(it != layouts.end())
{
layout_tuple += *it ? "ck::tensor_layout::gemm::ColumnMajor" : "ck::tensor_layout::gemm::RowMajor";
layout_tuple +=
*it ? "ck::tensor_layout::gemm::ColumnMajor" : "ck::tensor_layout::gemm::RowMajor";
it = std::next(it);
if (it != layouts.end())
if(it != layouts.end())
layout_tuple += ", ";
}
......@@ -85,7 +85,7 @@ std::string MakeTypeTuple(const std::vector<DataType>& types)
{
type_tuple += ToString(*it);
it = std::next(it);
if (it != types.end())
if(it != types.end())
type_tuple += ", ";
}
return type_tuple + ">";
......@@ -98,14 +98,16 @@ Solution Problem::MakeSolution(std::size_t idx, const std::string& arch) const
std::vector<std::string> params(std::istream_iterator<std::string>{iss},
std::istream_iterator<std::string>());
if (ADataType == DataType::Int8 and BDataType == DataType::Int8)
if(ADataType == DataType::Int8 and BDataType == DataType::Int8)
{
// Change CBlockTransfer ScalarPerVector if Ds contains other types
if (std::any_of(DsDataType.begin(), DsDataType.end(), [](auto t) { return t == DataType::Half; }))
if(std::any_of(
DsDataType.begin(), DsDataType.end(), [](auto t) { return t == DataType::Half; }))
{
params[params.size() - 3] = "8";
}
if (std::any_of(DsDataType.begin(), DsDataType.end(), [](auto t) { return t == DataType::Float; }))
if(std::any_of(
DsDataType.begin(), DsDataType.end(), [](auto t) { return t == DataType::Float; }))
{
params[params.size() - 3] = "4";
}
......@@ -128,10 +130,11 @@ Solution Problem::MakeSolution(std::size_t idx, const std::string& arch) const
const std::size_t grid_size = GetGridSize(M, N, m_per_block, n_per_block);
params[gemm_spec_idx] = GetGemmSpec(M, N, K, m_per_block, n_per_block, k_per_block);
std::string str = std::accumulate(params.begin() + 1, params.end(), std::string{},
[](const std::string& a, const std::string& b) {
return a.empty() ? b : a + ", " + b;
});
std::string str = std::accumulate(
params.begin() + 1,
params.end(),
std::string{},
[](const std::string& a, const std::string& b) { return a.empty() ? b : a + ", " + b; });
str = params.front() + "< " + str + ">";
return Solution{str, block_size, grid_size};
......@@ -146,7 +149,7 @@ std::vector<Solution> Problem::GetSolutions(const std::string& arch) const
{
std::vector<Solution> solutions;
const std::size_t num_instances = GetInstances(arch).size();
for (std::size_t i = 0; i < num_instances; ++i)
for(std::size_t i = 0; i < num_instances; ++i)
{
solutions.push_back(MakeSolution(i, arch));
}
......@@ -154,7 +157,6 @@ std::vector<Solution> Problem::GetSolutions(const std::string& arch) const
return solutions;
}
} // namespace device_gemm_multiple_d
} // namespace host
} // namespace ck
test/jit_library/jit_library.cpp
View file @ 77190058
......@@ -3,7 +3,8 @@
bool test_Problem()
{
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
false,
......@@ -27,9 +28,20 @@ bool test_Problem()
bool pass = true;
pass &= include_header == "ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_xdl_cshuffle.hpp";
pass &= include_header ==
"ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_xdl_cshuffle.hpp";
pass &= solutions.size() == 42;
pass &= template_str == "ck::tensor_operation::device::DeviceGemmMultipleD_Xdl_CShuffle< ck::tensor_layout::gemm::RowMajor, ck::tensor_layout::gemm::ColumnMajor, ck::Tuple<>, ck::tensor_layout::gemm::RowMajor, ck::half_t, ck::half_t, float, float, ck::Tuple<>, ck::half_t, ck::tensor_operation::element_wise::Passthrough, ck::tensor_operation::element_wise::Passthrough, ck::tensor_operation::element_wise::Passthrough, ck::tensor_operation::device::GemmSpecialization::Default, 1, 256, 256, 128, 32, 8, 8, 32, 32, 4, 2, ck::Sequence<4,64,1>, ck::Sequence<1,0,2>, ck::Sequence<1,0,2>, 2, 8, 8, 1, ck::Sequence<4,64,1>, ck::Sequence<1,0,2>, ck::Sequence<1,0,2>, 2, 8, 8, 1, 1, 1, ck::Sequence<1,32,1,8>, 8, ck::LoopScheduler::Default, ck::PipelineVersion::v1>";
pass &= template_str ==
"ck::tensor_operation::device::DeviceGemmMultipleD_Xdl_CShuffle< "
"ck::tensor_layout::gemm::RowMajor, ck::tensor_layout::gemm::ColumnMajor, ck::Tuple<>, "
"ck::tensor_layout::gemm::RowMajor, ck::half_t, ck::half_t, float, float, ck::Tuple<>, "
"ck::half_t, ck::tensor_operation::element_wise::Passthrough, "
"ck::tensor_operation::element_wise::Passthrough, "
"ck::tensor_operation::element_wise::Passthrough, "
"ck::tensor_operation::device::GemmSpecialization::Default, 1, 256, 256, 128, 32, 8, "
"8, 32, 32, 4, 2, ck::Sequence<4,64,1>, ck::Sequence<1,0,2>, ck::Sequence<1,0,2>, 2, "
"8, 8, 1, ck::Sequence<4,64,1>, ck::Sequence<1,0,2>, ck::Sequence<1,0,2>, 2, 8, 8, 1, "
"1, 1, ck::Sequence<1,32,1,8>, 8, ck::LoopScheduler::Default, ck::PipelineVersion::v1>";
pass &= grid_size == 2;
pass &= block_size == 256;
......@@ -40,8 +52,9 @@ bool test_GetGemmSpec()
{
bool pass = true;
{
//PadMNK
auto problem = ck::host::device_gemm_multiple_d::Problem{255,
// PadMNK
auto problem = ck::host::device_gemm_multiple_d::Problem{
255,
255,
255,
false,
......@@ -62,8 +75,9 @@ bool test_GetGemmSpec()
pass &= template_str.find("GemmSpecialization::MNKPadding") != std::string::npos;
}
{
//Default
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
// Default
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
false,
......@@ -91,8 +105,9 @@ bool test_GetInstances()
{
bool pass = true;
{
//Col Col Fp16
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
// Col Col Fp16
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
true,
......@@ -109,8 +124,9 @@ bool test_GetInstances()
pass &= problem.GetSolutions("gfx90a").size() == 51;
}
{
//Col Row Fp16
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
// Col Row Fp16
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
true,
......@@ -127,8 +143,9 @@ bool test_GetInstances()
pass &= problem.GetSolutions("gfx90a").size() == 51;
}
{
//Row Col Fp16
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
// Row Col Fp16
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
false,
......@@ -145,8 +162,9 @@ bool test_GetInstances()
pass &= problem.GetSolutions("gfx90a").size() == 42;
}
{
//Row Row Int8
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
// Row Row Int8
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
false,
......@@ -163,8 +181,9 @@ bool test_GetInstances()
pass &= problem.GetSolutions("gfx90a").size() == 48;
}
{
//Col Col Int8
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
// Col Col Int8
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
true,
......@@ -181,8 +200,9 @@ bool test_GetInstances()
pass &= problem.GetSolutions("gfx90a").size() == 48;
}
{
//Col Row Int8
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
// Col Row Int8
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
true,
......@@ -199,8 +219,9 @@ bool test_GetInstances()
pass &= problem.GetSolutions("gfx90a").size() == 48;
}
{
//Row Col Int8
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
// Row Col Int8
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
false,
......@@ -217,8 +238,9 @@ bool test_GetInstances()
pass &= problem.GetSolutions("gfx90a").size() == 39;
}
{
//Row Row Int8
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
// Row Row Int8
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
false,
......@@ -243,7 +265,8 @@ bool test_MakeLayoutsTuple()
bool pass = true;
{
// Empty Tuple
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
false,
......@@ -264,7 +287,8 @@ bool test_MakeLayoutsTuple()
}
{
// RowColRow Tuple
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
false,
......@@ -281,7 +305,10 @@ bool test_MakeLayoutsTuple()
const auto solutions = problem.GetSolutions("gfx90a");
const auto& solution = solutions.at(0);
const auto template_str = solution.template_str;
pass &= template_str.find("ck::Tuple<ck::tensor_layout::gemm::RowMajor, ck::tensor_layout::gemm::ColumnMajor, ck::tensor_layout::gemm::RowMajor>") != std::string::npos;
pass &= template_str.find(
"ck::Tuple<ck::tensor_layout::gemm::RowMajor, "
"ck::tensor_layout::gemm::ColumnMajor, ck::tensor_layout::gemm::RowMajor>") !=
std::string::npos;
}
return pass;
......@@ -292,7 +319,8 @@ bool test_MakeTypeTuple()
bool pass = true;
{
// Empty Tuple
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
false,
......@@ -313,7 +341,8 @@ bool test_MakeTypeTuple()
}
{
// Half Int8 Tuple
auto problem = ck::host::device_gemm_multiple_d::Problem{256,
auto problem = ck::host::device_gemm_multiple_d::Problem{
256,
256,
256,
false,
......
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