mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-04 05:31:24 +00:00
merge flatmm -scale
This commit is contained in:
lalala-sh
@@ -11,9 +11,9 @@
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#include "ck_tile/host.hpp"
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#include "flatmm_basic.hpp"
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#include "run_flatmm_example.inc"
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#include <type_traits>
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template <typename T>
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constexpr const char* DataTypeToString()
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{
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@@ -29,7 +29,7 @@ constexpr const char* DataTypeToString()
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{
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return "bf8";
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}
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else if constexpr(std::is_same_v<T, ck_tile::bf16_t>)
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else if constexpr(std::is_same_v<T, ck_tile::bf16_t>)
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{
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return "bf16";
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}
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@@ -84,70 +84,6 @@ auto calculate_rtol_atol(const ck_tile::index_t K,
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return ck_tile::make_tuple(std::max(rtol, rtol_split_k), std::max(atol, atol_split_k));
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}
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template <typename FlatmmConfig,
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typename ADataType,
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typename BDataType,
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typename DsDatatype,
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typename AccDataType,
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typename CDataType,
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typename ALayout,
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typename BLayout,
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typename DsLayout,
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typename CLayout,
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typename CDEElementWise = ck_tile::element_wise::PassThrough>
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float invoke_flatmm(ck_tile::DeviceMem& a_dev_buf,
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ck_tile::DeviceMem& b_shuffle_dev_buf,
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ck_tile::DeviceMem& c_dev_buf,
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ck_tile::index_t M,
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ck_tile::index_t N,
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ck_tile::index_t K,
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ck_tile::index_t stride_A,
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ck_tile::index_t stride_B,
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ck_tile::index_t stride_C,
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ck_tile::index_t kbatch,
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int n_warmup,
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int n_repeat)
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{
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ck_tile::FlatmmHostArgs<> args = {a_dev_buf.GetDeviceBuffer(),
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b_shuffle_dev_buf.GetDeviceBuffer(),
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{},
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c_dev_buf.GetDeviceBuffer(),
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kbatch,
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M,
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N,
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K,
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stride_A,
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stride_B,
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{},
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stride_C};
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float ave_time = flatmm_calc<FlatmmConfig,
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ADataType,
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BDataType,
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DsDatatype,
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AccDataType,
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CDataType,
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ALayout,
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BLayout,
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DsLayout,
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CLayout,
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false,
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CDEElementWise>(
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args, ck_tile::stream_config{nullptr, true, 1, n_warmup, n_repeat, true, true, 50});
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std::size_t flop = std::size_t(2) * M * N * K;
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std::size_t num_byte =
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sizeof(ADataType) * M * K + sizeof(BDataType) * N * K + sizeof(CDataType) * M * N;
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float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
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float gb_per_sec = num_byte / 1.E6 / ave_time;
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std::cout << "Run Flatmm kernel with DataType = " << DataTypeToString<ADataType>()
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<< " M =" << M << " N =" << N << " K =" << K << " StrideA =" << stride_A
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<< " StrideB =" << stride_B << " StrideC =" << stride_C << " : " << ave_time
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<< " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, " << std::endl;
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return ave_time;
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}
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template <typename FlatmmConfig,
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typename ADataType,
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@@ -159,9 +95,12 @@ template <typename FlatmmConfig,
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typename BLayout,
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typename DsLayout,
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typename ELayout,
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typename ScaleM,
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typename ScaleN,
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bool persistent,
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typename CDEElementWise>
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float flatmm_calc(const ck_tile::FlatmmHostArgs<>& args, const ck_tile::stream_config& s)
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float flatmm_calc(const ck_tile::ScaleFlatmmHostArgs<ScaleM, ScaleN>& args,
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const ck_tile::stream_config& s)
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{
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using CodegenFlatmmShape = ck_tile::TileGemmShape<
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ck_tile::sequence<FlatmmConfig::M_Tile, FlatmmConfig::N_Tile, FlatmmConfig::K_Tile>,
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@@ -217,13 +156,13 @@ float flatmm_calc(const ck_tile::FlatmmHostArgs<>& args, const ck_tile::stream_c
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constexpr auto memory_operation = memory_operation_.value;
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using CodegenPipelineProblem = ck_tile::FlatmmPipelineProblem<ADataType,
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BDataType,
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AccDataType,
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CodegenFlatmmShape,
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CodegenGemmTraits,
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scheduler,
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has_hot_loop_v,
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tail_number_v>;
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BDataType,
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AccDataType,
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CodegenFlatmmShape,
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CodegenGemmTraits,
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scheduler,
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has_hot_loop_v,
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tail_number_v>;
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using CodegenFlatmmPipeline =
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ck_tile::FlatmmPipelineAGmemBGmemCRegV0<CodegenPipelineProblem>;
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@@ -340,6 +279,79 @@ float flatmm_calc(const ck_tile::FlatmmHostArgs<>& args, const ck_tile::stream_c
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return ave_time;
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}
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template <typename FlatmmConfig,
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typename ADataType,
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typename BDataType,
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typename DsDatatype,
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typename AccDataType,
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typename CDataType,
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typename ALayout,
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typename BLayout,
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typename DsLayout,
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typename CLayout,
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typename ScaleM,
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typename ScaleN,
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typename CDEElementWise = ck_tile::element_wise::PassThrough>
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float invoke_flatmm(ck_tile::DeviceMem& a_dev_buf,
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ck_tile::DeviceMem& b_shuffle_dev_buf,
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ck_tile::DeviceMem& c_dev_buf,
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ck_tile::index_t M,
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ck_tile::index_t N,
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ck_tile::index_t K,
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ck_tile::index_t stride_A,
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ck_tile::index_t stride_B,
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ck_tile::index_t stride_C,
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ck_tile::index_t kbatch,
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ScaleM scale_m,
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ScaleN scale_n,
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int n_warmup,
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int n_repeat)
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{
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ck_tile::ScaleFlatmmHostArgs<ScaleM, ScaleN> args = {a_dev_buf.GetDeviceBuffer(),
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b_shuffle_dev_buf.GetDeviceBuffer(),
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{},
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c_dev_buf.GetDeviceBuffer(),
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kbatch,
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M,
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N,
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K,
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stride_A,
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stride_B,
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{},
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stride_C,
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scale_m,
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scale_n};
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float ave_time = flatmm_calc<FlatmmConfig,
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ADataType,
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BDataType,
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DsDatatype,
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AccDataType,
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CDataType,
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ALayout,
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BLayout,
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DsLayout,
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CLayout,
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ScaleM,
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ScaleN,
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false,
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CDEElementWise>(
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args, ck_tile::stream_config{nullptr, true, 1, n_warmup, n_repeat, true, true, 50});
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std::size_t flop = std::size_t(2) * M * N * K;
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std::size_t num_byte =
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sizeof(ADataType) * M * K + sizeof(BDataType) * N * K + sizeof(CDataType) * M * N;
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float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
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float gb_per_sec = num_byte / 1.E6 / ave_time;
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std::cout << "Run Flatmm kernel with DataType = " << DataTypeToString<ADataType>()
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<< " M =" << M << " N =" << N << " K =" << K << " StrideA =" << stride_A
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<< " StrideB =" << stride_B << " StrideC =" << stride_C << " : " << ave_time
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<< " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, " << std::endl;
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return ave_time;
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}
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auto create_args(int argc, char* argv[])
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{
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ck_tile::ArgParser arg_parser;
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@@ -360,6 +372,7 @@ auto create_args(int argc, char* argv[])
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.insert("timer", "gpu", "gpu:gpu timer, cpu:cpu timer")
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.insert("split_k", "1", "splitK value")
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.insert("init", "0", "0:random, 1:linear, 2:constant(1)")
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.insert("scale", "0", "0:without scale, 1:per-token/channel scale, only for fp8/bf8")
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.insert("warp_tile",
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"0",
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"0: 16x16, 1: 32x32, 2: 16x16x128 (950 only), 3: 32x32x64 (950 only)");
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@@ -367,6 +380,8 @@ auto create_args(int argc, char* argv[])
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return std::make_tuple(result, arg_parser);
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}
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#include "run_flatmm_example.inc"
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template <template <typename PreType> typename FlatmmConfig>
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int run_flatmm_example(int argc, char* argv[])
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{
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@@ -380,6 +395,7 @@ int run_flatmm_example(int argc, char* argv[])
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std::string data_type = arg_parser.get_str("prec");
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std::string a_layout = arg_parser.get_str("a_layout");
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std::string b_layout = arg_parser.get_str("b_layout");
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int scale_opt = arg_parser.get_int("scale");
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if(a_layout == "R" && b_layout == "C")
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{
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if(data_type == "fp16")
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@@ -394,13 +410,29 @@ int run_flatmm_example(int argc, char* argv[])
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}
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else if(data_type == "fp8")
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{
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run_flatmm_example_with_layouts<ck_tile::fp8_t, FlatmmConfig<ck_tile::fp8_t>>(
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argc, argv, Row{}, Col{}, Row{});
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if(scale_opt == 0)
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{
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run_flatmm_example_with_layouts<ck_tile::fp8_t, FlatmmConfig<ck_tile::fp8_t>>(
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argc, argv, Row{}, Col{}, Row{});
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}
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else
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{
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run_flatmm_example_with_layouts<ck_tile::fp8_t, FlatmmConfig<ck_tile::fp8_t>, 1, 1>(
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argc, argv, Row{}, Col{}, Row{});
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}
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}
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else if(data_type == "bf8")
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{
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run_flatmm_example_with_layouts<ck_tile::bf8_t, FlatmmConfig<ck_tile::bf8_t>>(
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argc, argv, Row{}, Col{}, Row{});
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if(scale_opt == 0)
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{
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run_flatmm_example_with_layouts<ck_tile::bf8_t, FlatmmConfig<ck_tile::bf8_t>>(
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argc, argv, Row{}, Col{}, Row{});
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}
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else
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{
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run_flatmm_example_with_layouts<ck_tile::bf8_t, FlatmmConfig<ck_tile::bf8_t>, 1, 1>(
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argc, argv, Row{}, Col{}, Row{});
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}
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}
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else
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{
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