diff --git a/CMakeLists.txt b/CMakeLists.txt index e90f893de0..cd03961477 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -246,13 +246,13 @@ if(NOT WIN32 AND ${hip_VERSION_FLAT} GREATER 500500000) add_compile_options("SHELL: -mllvm --lsr-drop-solution=1") endif() endif() -if(NOT WIN32 AND ${hip_VERSION_FLAT} GREATER 600140090) - check_cxx_compiler_flag("-mllvm -enable-post-misched=0" HAS_ENABLE_POST_MISCHED) - if(HAS_ENABLE_POST_MISCHED) - message("Adding the enable-post-misched=0 compiler flag") - add_compile_options("SHELL: -mllvm -enable-post-misched=0") - endif() -endif() +# if(NOT WIN32 AND ${hip_VERSION_FLAT} GREATER 600140090) +# check_cxx_compiler_flag("-mllvm -enable-post-misched=0" HAS_ENABLE_POST_MISCHED) +# if(HAS_ENABLE_POST_MISCHED) +# message("Adding the enable-post-misched=0 compiler flag") +# add_compile_options("SHELL: -mllvm -enable-post-misched=0") +# endif() +# endif() set(check-coerce) check_cxx_compiler_flag(" -mllvm -amdgpu-coerce-illegal-types=1" check-coerce) if(NOT WIN32 AND check-coerce AND ${hip_VERSION_FLAT} GREATER 600241132) diff --git a/example/65_gemm_multiply_multiply/CMakeLists.txt b/example/65_gemm_multiply_multiply/CMakeLists.txt index 55c884246f..4e916df773 100644 --- a/example/65_gemm_multiply_multiply/CMakeLists.txt +++ b/example/65_gemm_multiply_multiply/CMakeLists.txt @@ -1,4 +1,10 @@ add_example_executable(example_gemm_multiply_multiply_xdl_fp8 gemm_multiply_multiply_xdl_fp8.cpp) add_example_executable(example_gemm_multiply_multiply_xdl_fp8_ab_scale gemm_multiply_multiply_xdl_fp8_ab_scale.cpp) add_example_executable(example_gemm_add_add_xdl_fp16 gemm_add_add_xdl_fp16.cpp) -add_example_executable(example_gemm_multiply_multiply_xdl_int8 gemm_multiply_multiply_xdl_int8.cpp) \ No newline at end of file +add_example_executable(example_gemm_multiply_multiply_xdl_int8 gemm_multiply_multiply_xdl_int8.cpp) + +list(APPEND TILE_EXAPMLE_BLOCKSCALE_COMPILE_OPTIONS -mllvm -greedy-reverse-local-assignment=1) +list(APPEND TILE_EXAPMLE_BLOCKSCALE_COMPILE_OPTIONS -v --save-temps -Wno-gnu-line-marker) + +target_compile_options(example_gemm_multiply_multiply_xdl_fp8_ab_scale PRIVATE ${TILE_EXAPMLE_BLOCKSCALE_COMPILE_OPTIONS}) +target_compile_options(example_gemm_multiply_multiply_xdl_fp8 PRIVATE ${TILE_EXAPMLE_BLOCKSCALE_COMPILE_OPTIONS}) \ No newline at end of file diff --git a/example/65_gemm_multiply_multiply/gemm_multiply_multiply_xdl_fp8.cpp b/example/65_gemm_multiply_multiply/gemm_multiply_multiply_xdl_fp8.cpp index 18f78851dc..3c12b733ac 100644 --- a/example/65_gemm_multiply_multiply/gemm_multiply_multiply_xdl_fp8.cpp +++ b/example/65_gemm_multiply_multiply/gemm_multiply_multiply_xdl_fp8.cpp @@ -72,7 +72,7 @@ using AElementOp = PassThrough; using BElementOp = PassThrough; using CDEElementOp = MultiplyMultiply; -static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNPadding; +static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::Default; using DeviceOpInstance = ck::tensor_operation::device::DeviceGemmMultiD_Xdl_CShuffle_V3 // clang-format off @@ -86,7 +86,18 @@ using DeviceOpInstance = ck::tensor_operation::device::DeviceGemmMultiD_Xdl_CShu // kernel 1: 256->32x128x128 // < Row, Col, DsLayout, ELayout, A0DataType, B0DataType, DsDataType, EDataType, AccDataType, CShuffleDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 256, 32, 128, 128, 16, 16, 32, 32, 1, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, ck::BlockGemmPipelineScheduler::Interwave, ck::BlockGemmPipelineVersion::v1, FP8>; // kernel 2: 128->32x128x128 - < Row, Col, DsLayout, ELayout, A0DataType, B0DataType, DsDataType, EDataType, AccDataType, CShuffleDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 128, 32, 128, 128, 16, 16, 32, 32, 1, 2, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, 1, 1, S<1, 16, 1, 8>, S<8, 8, 1>, ck::BlockGemmPipelineScheduler::Interwave, ck::BlockGemmPipelineVersion::v1, FP8>; + < Row, Col, DsLayout, ELayout, + A0DataType, B0DataType, DsDataType, EDataType, AccDataType, CShuffleDataType, + AElementOp, BElementOp, CDEElementOp, GemmSpec, + 256, + 128, 128, + 128, 16, 16, + 32, 32, + 2, 2, + S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, + S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, + 1, 1, S<1, 32, 1, 8>, S<8, 8, 1>, + ck::BlockGemmPipelineScheduler::Intrawave, ck::BlockGemmPipelineVersion::v3, FP8>; // clang-format on int main(int argc, char* argv[]) diff --git a/example/65_gemm_multiply_multiply/gemm_multiply_multiply_xdl_fp8_ab_scale.cpp b/example/65_gemm_multiply_multiply/gemm_multiply_multiply_xdl_fp8_ab_scale.cpp index 55bdb76b9a..76ebe93c36 100644 --- a/example/65_gemm_multiply_multiply/gemm_multiply_multiply_xdl_fp8_ab_scale.cpp +++ b/example/65_gemm_multiply_multiply/gemm_multiply_multiply_xdl_fp8_ab_scale.cpp @@ -53,7 +53,7 @@ using AElementOp = PassThrough; using BElementOp = PassThrough; using CDEElementOp = PassThrough; -static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding; +static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::Default; static constexpr ck::index_t Scale_Block_M = 1; static constexpr ck::index_t Scale_Block_N = 128; @@ -67,12 +67,12 @@ using DeviceOpInstance = ck::tensor_operation::device::DeviceGemmMultiD_ABScale_ 256, Scale_Block_M, Scale_Block_N, Scale_Block_K, 128, 128, 128, 16, 16, - 16, 16, - 4, 4, + 32, 32, + 2, 2, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 0, - 1, 2, S<1, 32, 1, 8>, S<8>, - ck::BlockGemmPipelineScheduler::Intrawave, ck::BlockGemmPipelineVersion::v1, FP8>; + 1, 1, S<1, 32, 1, 8>, S<8>, + ck::BlockGemmPipelineScheduler::Intrawave, ck::BlockGemmPipelineVersion::v3, FP8>; // clang-format on int main(int argc, char* argv[]) diff --git a/include/ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_v1_ab_scale.hpp b/include/ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_v1_ab_scale.hpp index 58823214fb..02bc0a941c 100644 --- a/include/ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_v1_ab_scale.hpp +++ b/include/ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_v1_ab_scale.hpp @@ -240,18 +240,18 @@ struct BlockwiseGemmXdlops_pipeline_v1_ab_scale{})); + a_scale_thread_copy_step.At(Number<0>{})); }); if(num_loop_per_scale == 1) { a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, - a_scale_thread_copy_step.At(Number<2>{})); + a_scale_thread_copy_step.At(Number<2>{})); } else { a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, - a_scale_thread_copy_step.At(Number<1>{})); + a_scale_thread_copy_step.At(Number<1>{})); } b_scale_thread_copy.Run(b_scale_grid_desc, @@ -346,19 +346,19 @@ struct BlockwiseGemmXdlops_pipeline_v1_ab_scale{})); + a_scale_thread_copy.MoveSrcSliceWindow( + a_scale_grid_desc, a_scale_thread_copy_step.At(Number<0>{})); }); if(num_loop_per_scale == 1) { - a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, - a_scale_thread_copy_step.At(Number<2>{})); + a_scale_thread_copy.MoveSrcSliceWindow( + a_scale_grid_desc, a_scale_thread_copy_step.At(Number<2>{})); } else { - a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, - a_scale_thread_copy_step.At(Number<1>{})); + a_scale_thread_copy.MoveSrcSliceWindow( + a_scale_grid_desc, a_scale_thread_copy_step.At(Number<1>{})); } b_scale_thread_copy.Run(b_scale_grid_desc, diff --git a/include/ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_v2_ab_scale.hpp b/include/ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_v2_ab_scale.hpp index 5ed36ac1c0..c8ad9c5b02 100644 --- a/include/ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_v2_ab_scale.hpp +++ b/include/ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_v2_ab_scale.hpp @@ -388,19 +388,19 @@ struct BlockwiseGemmXdlops_pipeline_v2_ab_scale{})); + a_scale_thread_copy.MoveSrcSliceWindow( + a_scale_grid_desc, a_scale_thread_copy_step.At(Number<0>{})); }); if(num_loop_per_scale == 1) { - a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, - a_scale_thread_copy_step.At(Number<2>{})); + a_scale_thread_copy.MoveSrcSliceWindow( + a_scale_grid_desc, a_scale_thread_copy_step.At(Number<2>{})); } else { - a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, - a_scale_thread_copy_step.At(Number<1>{})); + a_scale_thread_copy.MoveSrcSliceWindow( + a_scale_grid_desc, a_scale_thread_copy_step.At(Number<1>{})); } b_scale_thread_copy.Run(b_scale_grid_desc, @@ -494,19 +494,19 @@ struct BlockwiseGemmXdlops_pipeline_v2_ab_scale{})); + a_scale_thread_copy.MoveSrcSliceWindow( + a_scale_grid_desc, a_scale_thread_copy_step.At(Number<0>{})); }); if(num_loop_per_scale == 1) { - a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, - a_scale_thread_copy_step.At(Number<2>{})); + a_scale_thread_copy.MoveSrcSliceWindow( + a_scale_grid_desc, a_scale_thread_copy_step.At(Number<2>{})); } else { - a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, - a_scale_thread_copy_step.At(Number<1>{})); + a_scale_thread_copy.MoveSrcSliceWindow( + a_scale_grid_desc, a_scale_thread_copy_step.At(Number<1>{})); } b_scale_thread_copy.Run(b_scale_grid_desc, diff --git a/include/ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_v3_ab_scale.hpp b/include/ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_v3_ab_scale.hpp index 2f195fa058..dbbc27d706 100644 --- a/include/ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_v3_ab_scale.hpp +++ b/include/ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_v3_ab_scale.hpp @@ -179,11 +179,11 @@ struct BlockwiseGemmXdlops_pipeline_v3_ab_scale( a_thread_desc_.GetElementSpaceSize()); auto b_thread_buf = make_static_buffer( @@ -332,6 +333,8 @@ struct BlockwiseGemmXdlops_pipeline_v3_ab_scale( b_scale_thread_desc.GetElementSpaceSize()); + auto c_scale_thread_buf = make_static_buffer( + c_scale_thread_desc.GetElementSpaceSize()); // Global prefetch 1 a_blockwise_copy.RunRead(a_grid_desc, a_grid_buf); @@ -340,12 +343,6 @@ struct BlockwiseGemmXdlops_pipeline_v3_ab_scale{}([&](auto m0) { a_scale_thread_copy.Run(a_scale_grid_desc, a_scale_grid_buf, @@ -356,7 +353,7 @@ struct BlockwiseGemmXdlops_pipeline_v3_ab_scale{})); }); - if(num_loop_per_scale == 1) + if constexpr(NumKBlockPerScale == 1) { a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, a_scale_thread_copy_step.At(Number<2>{})); @@ -375,6 +372,11 @@ struct BlockwiseGemmXdlops_pipeline_v3_ab_scale{}([&](auto m0) { + c_scale_thread_buf(m0) = a_scale_thread_buf[m0] * b_scale_thread_buf[I0]; + }); + // Local prefill 1 a_blockwise_copy.RunWrite(a_block_desc, a_block_buf); b_blockwise_copy.RunWrite(b_block_desc, b_block_buf); @@ -386,10 +388,42 @@ struct BlockwiseGemmXdlops_pipeline_v3_ab_scale{}([&](auto m0) { + a_scale_thread_copy.Run(a_scale_grid_desc, + a_scale_grid_buf, + a_scale_thread_desc, + make_tuple(m0, I0), + a_scale_thread_buf); + a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, + a_scale_thread_copy_step.At(Number<0>{})); + }); + + if constexpr(NumKBlockPerScale == 1) + { + a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, + a_scale_thread_copy_step.At(Number<2>{})); + } + else + { + a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, + a_scale_thread_copy_step.At(Number<1>{})); + } + + b_scale_thread_copy.Run(b_scale_grid_desc, + b_scale_grid_buf, + b_scale_thread_desc, + make_tuple(I0, I0), + b_scale_thread_buf); + // Initialize C c_thread_buf.Clear(); - auto c_thread_buf_per_scale = remove_cvref_t(); + StaticBufferTupleOfVector + c_thread_buf_per_scale; // Local prefetch 1 block_sync_lds(); @@ -432,7 +466,10 @@ struct BlockwiseGemmXdlops_pipeline_v3_ab_scale{}([&](auto m0) { static_for<0, NRepeat, 1>{}([&](auto n0) { - c_thread_buf_per_scale.Clear(); + static_for<0, xdlops_gemm.GetRegSizePerXdlops(), 1>{}([&](auto t) { + c_thread_buf_per_scale.GetVectorTypeReference(Number<0>{}) + .template AsType()(Number{}) = 0; + }); static_for<0, KRepeat, 1>{}([&](auto k0) { vector_type a_thread_vec; vector_type b_thread_vec; @@ -453,19 +490,23 @@ struct BlockwiseGemmXdlops_pipeline_v3_ab_scale( a_thread_vec.template AsType(), b_thread_vec.template AsType(), - c_thread_buf_per_scale.GetVectorTypeReference(I0)); + c_thread_buf_per_scale.GetVectorTypeReference(Number<0>{})); }); static_for<0, xdlops_gemm.GetRegSizePerXdlops(), 1>{}([&](auto t) { constexpr index_t c_offset = c_thread_desc_.CalculateOffset(make_tuple(m0, n0, t)); c_thread_buf(Number{}) += - c_thread_buf_per_scale[Number{}] * - type_convert(a_scale_thread_buf[m0]) * - type_convert(b_scale_thread_buf[I0]); + c_thread_buf_per_scale.GetVectorTypeReference(Number<0>{}) + .template AsType()[Number{}] * + type_convert(c_scale_thread_buf[m0]); }); }); }); + static_for<0, MRepeat, 1>{}([&](auto m0) { + c_scale_thread_buf(m0) = a_scale_thread_buf[m0] * b_scale_thread_buf[I0]; + }); + block_sync_lds(); static_for<0, KRepeat, 1>{}([&](auto k) { static_for<0, MRepeat, 1>{}([&](auto m0) { @@ -485,11 +526,6 @@ struct BlockwiseGemmXdlops_pipeline_v3_ab_scale{}([&](auto m0) { a_scale_thread_copy.Run(a_scale_grid_desc, @@ -497,19 +533,19 @@ struct BlockwiseGemmXdlops_pipeline_v3_ab_scale{})); + a_scale_thread_copy.MoveSrcSliceWindow( + a_scale_grid_desc, a_scale_thread_copy_step.At(Number<0>{})); }); - if(num_loop_per_scale == 1) + if constexpr(NumKBlockPerScale == 1) { - a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, - a_scale_thread_copy_step.At(Number<2>{})); + a_scale_thread_copy.MoveSrcSliceWindow( + a_scale_grid_desc, a_scale_thread_copy_step.At(Number<2>{})); } else { - a_scale_thread_copy.MoveSrcSliceWindow(a_scale_grid_desc, - a_scale_thread_copy_step.At(Number<1>{})); + a_scale_thread_copy.MoveSrcSliceWindow( + a_scale_grid_desc, a_scale_thread_copy_step.At(Number<1>{})); } b_scale_thread_copy.Run(b_scale_grid_desc, @@ -518,7 +554,6 @@ struct BlockwiseGemmXdlops_pipeline_v3_ab_scale{}([&](auto m0) { static_for<0, NRepeat, 1>{}([&](auto n0) { - c_thread_buf_per_scale.Clear(); + static_for<0, xdlops_gemm.GetRegSizePerXdlops(), 1>{}([&](auto t) { + c_thread_buf_per_scale.GetVectorTypeReference(Number<0>{}) + .template AsType()(Number{}) = 0; + }); static_for<0, KRepeat, 1>{}([&](auto k0) { vector_type a_thread_vec; vector_type b_thread_vec; @@ -551,15 +589,15 @@ struct BlockwiseGemmXdlops_pipeline_v3_ab_scale( a_thread_vec.template AsType(), b_thread_vec.template AsType(), - c_thread_buf_per_scale.GetVectorTypeReference(I0)); + c_thread_buf_per_scale.GetVectorTypeReference(Number<0>{})); }); static_for<0, xdlops_gemm.GetRegSizePerXdlops(), 1>{}([&](auto t) { constexpr index_t c_offset = c_thread_desc_.CalculateOffset(make_tuple(m0, n0, t)); c_thread_buf(Number{}) += - c_thread_buf_per_scale[Number{}] * - type_convert(a_scale_thread_buf[m0]) * - type_convert(b_scale_thread_buf[I0]); + c_thread_buf_per_scale.GetVectorTypeReference(Number<0>{}) + .template AsType()[Number{}] * + type_convert(c_scale_thread_buf[m0]); }); }); }); diff --git a/include/ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_xdl_cshuffle_v3_ab_scale.hpp b/include/ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_xdl_cshuffle_v3_ab_scale.hpp index 9ddde91145..adc0f749e2 100644 --- a/include/ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_xdl_cshuffle_v3_ab_scale.hpp +++ b/include/ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_xdl_cshuffle_v3_ab_scale.hpp @@ -363,7 +363,8 @@ struct DeviceGemmMultiD_ABScale_Xdl_CShuffle_V3 return false; } - // if(ScaleBlockM % MPerBlock != 0 || ScaleBlockN % NPerBlock != 0 || ScaleBlockK != KPerBlock) + // if(ScaleBlockM % MPerBlock != 0 || ScaleBlockN % NPerBlock != 0 || ScaleBlockK != + // KPerBlock) // { // return false; // } diff --git a/include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_cshuffle_v3_multi_d.hpp b/include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_cshuffle_v3_multi_d.hpp index e5a31f8d1f..d1f6cdde22 100644 --- a/include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_cshuffle_v3_multi_d.hpp +++ b/include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_cshuffle_v3_multi_d.hpp @@ -686,40 +686,19 @@ struct GridwiseGemmMultiD_xdl_cshuffle_v3 // in some cases. else if constexpr(is_same::value) { - constexpr auto MLdsLayer = 32 * 4 / KPerBlock / sizeof(LDSTypeA) < 1 - ? 1 - : 32 * 4 / KPerBlock / sizeof(LDSTypeA); - constexpr auto a_lds_block_desc = make_naive_tensor_descriptor( - make_tuple( - AK0Number * Number{}, Number{}, AK1Number), - make_tuple(AK1Number, Number{}, I1)); + constexpr auto a_lds_block_desc = + make_naive_tensor_descriptor(make_tuple(AK0Number, Number{}, AK1Number), + make_tuple(AK1Number, Number{}, I1)); constexpr auto a_lds_block_desc_permuted = transform_tensor_descriptor( a_lds_block_desc, - make_tuple(make_xor_with_modulo_transform(make_tuple( - Number{}, Number{})), + make_tuple(make_xor_with_modulo_transform( + make_tuple(Number{}, Number{})), make_pass_through_transform(AK1Number)), make_tuple(Sequence<1, 0>{}, Sequence<2>{}), make_tuple(Sequence<1, 0>{}, Sequence<2>{})); - constexpr auto a_lds_block_desc_ak0_mldslayer_m_ak1 = transform_tensor_descriptor( - a_lds_block_desc_permuted, - make_tuple(make_unmerge_transform(make_tuple(AK0Number, Number{})), - make_pass_through_transform(Number{}), - make_pass_through_transform(AK1Number)), - make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}), - make_tuple(Sequence<0, 2>{}, Sequence<1>{}, Sequence<3>{})); - - constexpr auto a_lds_block_desc_ak0_m_ak1 = transform_tensor_descriptor( - a_lds_block_desc_ak0_mldslayer_m_ak1, - make_tuple(make_pass_through_transform(AK0Number), - make_merge_transform_v3_division_mod( - make_tuple(Number{}, Number{})), - make_pass_through_transform(AK1Number)), - make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3>{}), - make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{})); - - return a_lds_block_desc_ak0_m_ak1; + return a_lds_block_desc_permuted; } else // ColumnMajor A { @@ -821,42 +800,19 @@ struct GridwiseGemmMultiD_xdl_cshuffle_v3 } else if constexpr(is_same::value) { - // NLdsLayer * K0 as logical Bank - constexpr auto NLdsLayer = 32 * 4 / KPerBlock / sizeof(LDSTypeB) < 1 - ? 1 - : 32 * 4 / KPerBlock / sizeof(LDSTypeB); - ; - constexpr auto b_lds_block_desc = make_naive_tensor_descriptor( - make_tuple( - BK0Number * Number{}, Number{}, BK1Number), - make_tuple(BK1Number, Number{}, I1)); + constexpr auto b_lds_block_desc = + make_naive_tensor_descriptor(make_tuple(BK0Number, Number{}, BK1Number), + make_tuple(BK1Number, Number{}, I1)); constexpr auto b_lds_block_desc_permuted = transform_tensor_descriptor( b_lds_block_desc, - make_tuple(make_xor_with_modulo_transform(make_tuple( - Number{}, Number{})), + make_tuple(make_xor_with_modulo_transform( + make_tuple(Number{}, Number{})), make_pass_through_transform(BK1Number)), make_tuple(Sequence<1, 0>{}, Sequence<2>{}), make_tuple(Sequence<1, 0>{}, Sequence<2>{})); - constexpr auto b_lds_block_desc_bk0_nldslayer_n_bk1 = transform_tensor_descriptor( - b_lds_block_desc_permuted, - make_tuple(make_unmerge_transform(make_tuple(BK0Number, Number{})), - make_pass_through_transform(Number{}), - make_pass_through_transform(BK1Number)), - make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}), - make_tuple(Sequence<0, 2>{}, Sequence<1>{}, Sequence<3>{})); - - constexpr auto b_lds_block_desc_bk0_n_bk1 = transform_tensor_descriptor( - b_lds_block_desc_bk0_nldslayer_n_bk1, - make_tuple(make_pass_through_transform(BK0Number), - make_merge_transform_v3_division_mod( - make_tuple(Number{}, Number{})), - make_pass_through_transform(BK1Number)), - make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3>{}), - make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{})); - - return b_lds_block_desc_bk0_n_bk1; + return b_lds_block_desc_permuted; } else // RowMajor B { diff --git a/include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_cshuffle_v3_multi_d_ab_scale.hpp b/include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_cshuffle_v3_multi_d_ab_scale.hpp index a1eb63f401..2710ab7a48 100644 --- a/include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_cshuffle_v3_multi_d_ab_scale.hpp +++ b/include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_cshuffle_v3_multi_d_ab_scale.hpp @@ -656,40 +656,19 @@ struct GridwiseGemmMultiD_ABScale_xdl_cshuffle_v3 // in some cases. else if constexpr(is_same::value) { - constexpr auto MLdsLayer = 32 * 4 / KPerBlock / sizeof(LDSTypeA) < 1 - ? 1 - : 32 * 4 / KPerBlock / sizeof(LDSTypeA); - constexpr auto a_lds_block_desc = make_naive_tensor_descriptor( - make_tuple( - AK0Number * Number{}, Number{}, AK1Number), - make_tuple(AK1Number, Number{}, I1)); + constexpr auto a_lds_block_desc = + make_naive_tensor_descriptor(make_tuple(AK0Number, Number{}, AK1Number), + make_tuple(AK1Number, Number{}, I1)); constexpr auto a_lds_block_desc_permuted = transform_tensor_descriptor( a_lds_block_desc, - make_tuple(make_xor_with_modulo_transform(make_tuple( - Number{}, Number{})), + make_tuple(make_xor_with_modulo_transform( + make_tuple(Number{}, Number{})), make_pass_through_transform(AK1Number)), make_tuple(Sequence<1, 0>{}, Sequence<2>{}), make_tuple(Sequence<1, 0>{}, Sequence<2>{})); - constexpr auto a_lds_block_desc_ak0_mldslayer_m_ak1 = transform_tensor_descriptor( - a_lds_block_desc_permuted, - make_tuple(make_unmerge_transform(make_tuple(AK0Number, Number{})), - make_pass_through_transform(Number{}), - make_pass_through_transform(AK1Number)), - make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}), - make_tuple(Sequence<0, 2>{}, Sequence<1>{}, Sequence<3>{})); - - constexpr auto a_lds_block_desc_ak0_m_ak1 = transform_tensor_descriptor( - a_lds_block_desc_ak0_mldslayer_m_ak1, - make_tuple(make_pass_through_transform(AK0Number), - make_merge_transform_v3_division_mod( - make_tuple(Number{}, Number{})), - make_pass_through_transform(AK1Number)), - make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3>{}), - make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{})); - - return a_lds_block_desc_ak0_m_ak1; + return a_lds_block_desc_permuted; } else // ColumnMajor A { @@ -791,42 +770,19 @@ struct GridwiseGemmMultiD_ABScale_xdl_cshuffle_v3 } else if constexpr(is_same::value) { - // NLdsLayer * K0 as logical Bank - constexpr auto NLdsLayer = 32 * 4 / KPerBlock / sizeof(LDSTypeB) < 1 - ? 1 - : 32 * 4 / KPerBlock / sizeof(LDSTypeB); - ; - constexpr auto b_lds_block_desc = make_naive_tensor_descriptor( - make_tuple( - BK0Number * Number{}, Number{}, BK1Number), - make_tuple(BK1Number, Number{}, I1)); + constexpr auto b_lds_block_desc = + make_naive_tensor_descriptor(make_tuple(BK0Number, Number{}, BK1Number), + make_tuple(BK1Number, Number{}, I1)); constexpr auto b_lds_block_desc_permuted = transform_tensor_descriptor( b_lds_block_desc, - make_tuple(make_xor_with_modulo_transform(make_tuple( - Number{}, Number{})), + make_tuple(make_xor_with_modulo_transform( + make_tuple(Number{}, Number{})), make_pass_through_transform(BK1Number)), make_tuple(Sequence<1, 0>{}, Sequence<2>{}), make_tuple(Sequence<1, 0>{}, Sequence<2>{})); - constexpr auto b_lds_block_desc_bk0_nldslayer_n_bk1 = transform_tensor_descriptor( - b_lds_block_desc_permuted, - make_tuple(make_unmerge_transform(make_tuple(BK0Number, Number{})), - make_pass_through_transform(Number{}), - make_pass_through_transform(BK1Number)), - make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}), - make_tuple(Sequence<0, 2>{}, Sequence<1>{}, Sequence<3>{})); - - constexpr auto b_lds_block_desc_bk0_n_bk1 = transform_tensor_descriptor( - b_lds_block_desc_bk0_nldslayer_n_bk1, - make_tuple(make_pass_through_transform(BK0Number), - make_merge_transform_v3_division_mod( - make_tuple(Number{}, Number{})), - make_pass_through_transform(BK1Number)), - make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3>{}), - make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{})); - - return b_lds_block_desc_bk0_n_bk1; + return b_lds_block_desc_permuted; } else // RowMajor B { @@ -1363,15 +1319,19 @@ struct GridwiseGemmMultiD_ABScale_xdl_cshuffle_v3 constexpr auto a_scale_thread_desc = make_naive_tensor_descriptor_packed( make_tuple(Number{}, Number{})); - + constexpr index_t MWaves = MPerBlock / (MXdlPerWave * MPerXdl); constexpr index_t NWaves = NPerBlock / (NXdlPerWave * NPerXdl); auto a_thread_offset = get_thread_local_1d_id() % MPerXdl + (get_thread_local_1d_id() / 64) / NWaves * MPerXdl; - // auto a_thread_offset = get_thread_local_1d_id() % MPerXdl + (get_thread_local_1d_id() / 128) * MPerXdl; + // auto a_thread_offset = get_thread_local_1d_id() % MPerXdl + (get_thread_local_1d_id() / + // 128) * MPerXdl; constexpr auto b_scale_thread_desc = make_naive_tensor_descriptor_packed( - make_tuple(Number{}, Number{})); + make_tuple(Number{}, Number{})); + + constexpr auto c_scale_thread_desc = make_naive_tensor_descriptor_packed(make_tuple( + Number{}, Number{}, Number{})); auto a_scale_thread_copy = ThreadwiseTensorSliceTransfer_v2( - a_scale_grid_desc_am_ak, + a_scale_grid_desc_am_ak, make_multi_index(block_m_id * MPerBlock / ScaleBlockM + a_thread_offset, 0)); auto b_scale_thread_copy = @@ -1407,9 +1367,9 @@ struct GridwiseGemmMultiD_ABScale_xdl_cshuffle_v3 make_multi_index(-MPerBlock, 1)); constexpr auto b_scale_thread_slice_copy_step = make_multi_index(0, 1); - const index_t num_k_block_per_scale = ScaleBlockK / KPerBlock; + constexpr auto NumKBlockPerScale = ScaleBlockK / KPerBlock; - blockwise_gemm_pipeline.template Run( + blockwise_gemm_pipeline.template Run( a_grid_desc_ak0_m_ak1, a_block_desc_ak0_m_ak1, a_blockwise_copy, @@ -1422,6 +1382,8 @@ struct GridwiseGemmMultiD_ABScale_xdl_cshuffle_v3 b_grid_buf, b_block_buf, b_block_slice_copy_step, + + c_scale_thread_desc, c_thread_buf, a_scale_grid_desc_am_ak, @@ -1436,8 +1398,7 @@ struct GridwiseGemmMultiD_ABScale_xdl_cshuffle_v3 b_scale_grid_buf, b_scale_thread_slice_copy_step, - num_k_block_main_loop, - num_k_block_per_scale); + num_k_block_main_loop); // shuffle C and write out { @@ -1447,7 +1408,7 @@ struct GridwiseGemmMultiD_ABScale_xdl_cshuffle_v3 constexpr index_t MWave = MPerBlock / (MXdlPerWave * MPerXdl); constexpr index_t NWave = NPerBlock / (NXdlPerWave * NPerXdl); - + // transposed XDL // // TODO: hacky, fix it! constexpr auto c_thread_desc_m0_n0_m1_n1_m2_n2_n3_n4 = @@ -1467,9 +1428,6 @@ struct GridwiseGemmMultiD_ABScale_xdl_cshuffle_v3 constexpr auto N3 = c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4_tmp.GetLength(I6); constexpr auto N4 = c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4_tmp.GetLength(I7); - - - constexpr auto c_shuffle_block_desc_mblock_mperblock_nblock_nperblock = GetCShuffleBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(); diff --git a/library/src/tensor_operation_instance/gpu/gemm_ab_scale/device_gemm_ab_scale_xdl_f8_f8_bf16/device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_128_128_128_mem_v1_default_instance.cpp b/library/src/tensor_operation_instance/gpu/gemm_ab_scale/device_gemm_ab_scale_xdl_f8_f8_bf16/device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_128_128_128_mem_v1_default_instance.cpp index a466bb23dd..569911e3de 100644 --- a/library/src/tensor_operation_instance/gpu/gemm_ab_scale/device_gemm_ab_scale_xdl_f8_f8_bf16/device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_128_128_128_mem_v1_default_instance.cpp +++ b/library/src/tensor_operation_instance/gpu/gemm_ab_scale/device_gemm_ab_scale_xdl_f8_f8_bf16/device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_128_128_128_mem_v1_default_instance.cpp @@ -29,7 +29,7 @@ void add_device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_1_128_128_mem_v1_default_i add_device_operation_instances( instances, device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_1_128_128_mem_instances{}); + GemmDefault>{}); } } // namespace instance diff --git a/library/src/tensor_operation_instance/gpu/gemm_ab_scale/device_gemm_ab_scale_xdl_f8_f8_bf16/device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_128_128_128_mem_v1_kpadding_instance.cpp b/library/src/tensor_operation_instance/gpu/gemm_ab_scale/device_gemm_ab_scale_xdl_f8_f8_bf16/device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_128_128_128_mem_v1_kpadding_instance.cpp index a1722fade8..d1e5b6b535 100644 --- a/library/src/tensor_operation_instance/gpu/gemm_ab_scale/device_gemm_ab_scale_xdl_f8_f8_bf16/device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_128_128_128_mem_v1_kpadding_instance.cpp +++ b/library/src/tensor_operation_instance/gpu/gemm_ab_scale/device_gemm_ab_scale_xdl_f8_f8_bf16/device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_128_128_128_mem_v1_kpadding_instance.cpp @@ -29,7 +29,7 @@ void add_device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_1_128_128_mem_v1_kpadding_ add_device_operation_instances( instances, device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_1_128_128_mem_instances{}); + GemmKPadding>{}); } } // namespace instance diff --git a/library/src/tensor_operation_instance/gpu/gemm_ab_scale/device_gemm_ab_scale_xdl_f8_f8_bf16/device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_128_128_128_mem_v1_mnkpadding_instance.cpp b/library/src/tensor_operation_instance/gpu/gemm_ab_scale/device_gemm_ab_scale_xdl_f8_f8_bf16/device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_128_128_128_mem_v1_mnkpadding_instance.cpp index 0f91fdefcc..f51fa43bcb 100644 --- a/library/src/tensor_operation_instance/gpu/gemm_ab_scale/device_gemm_ab_scale_xdl_f8_f8_bf16/device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_128_128_128_mem_v1_mnkpadding_instance.cpp +++ b/library/src/tensor_operation_instance/gpu/gemm_ab_scale/device_gemm_ab_scale_xdl_f8_f8_bf16/device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_128_128_128_mem_v1_mnkpadding_instance.cpp @@ -29,7 +29,7 @@ void add_device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_1_128_128_mem_v1_mnkpaddin add_device_operation_instances( instances, device_gemm_ab_scale_xdl_f8_f8_bf16_mk_nk_mn_1_128_128_mem_instances{}); + GemmMNKPadding>{}); } } // namespace instance diff --git a/profiler/src/profile_gemm_ab_scale.cpp b/profiler/src/profile_gemm_ab_scale.cpp index 1b46b07864..c17ab74536 100644 --- a/profiler/src/profile_gemm_ab_scale.cpp +++ b/profiler/src/profile_gemm_ab_scale.cpp @@ -35,7 +35,6 @@ enum struct ScaleBlockTile Tile_1_128_128, // 1 }; - #define OP_NAME "gemm_ab_scale" #define OP_DESC "GEMM_AB_Scale" diff --git a/script/cmake-ck-dev.sh b/script/cmake-ck-dev.sh index 6089fc7a7e..7d1d5e60e9 100755 --- a/script/cmake-ck-dev.sh +++ b/script/cmake-ck-dev.sh @@ -17,7 +17,7 @@ fi cmake \ -D CMAKE_PREFIX_PATH=/opt/rocm/ \ -D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc \ --D CMAKE_CXX_FLAGS="-Xclang -mllvm -Xclang -enable-post-misched=0 -std=c++17 -O3 -ftemplate-backtrace-limit=0 -fPIE -Wno-gnu-line-marker" \ +-D CMAKE_CXX_FLAGS="-std=c++17 -O3 -ftemplate-backtrace-limit=0 -fPIE -Wno-gnu-line-marker" \ -D CMAKE_BUILD_TYPE=Release \ -D BUILD_DEV=ON \ -D GPU_TARGETS=$GPU_TARGETS \