diff options
author | Ramy Elgammal <ramelg01@e111855.cambridge.arm.com> | 2022-02-01 23:01:27 +0000 |
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committer | Ramy Elgammal <ramy.elgammal@arm.com> | 2022-02-02 15:59:06 +0000 |
commit | 451c309179b784d19d333da31aec5a871c3ff2b6 (patch) | |
tree | faf44c49a95851f0069d37c880df6ad8aa2f779f /src/gpu/cl/kernels | |
parent | 46d44d26183d835d209d7ef1b9023e217dd4019d (diff) | |
download | ComputeLibrary-451c309179b784d19d333da31aec5a871c3ff2b6.tar.gz |
Revert "Rework gemm_mm_reshaped_only_rhs_ kernels with new macros"
This reverts commit 10e88a7351 "Rework gemm_mm_reshaped_only_rhs_ kernels with new macros"
Resolves: COMPMID-5095
Signed-off-by: Ramy Elgammal<ramy.elgammal@arm.com>
Change-Id: I46e167882f072e7508b6101d295accb6e089e740
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7045
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/gpu/cl/kernels')
-rw-r--r-- | src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedOnlyRhsKernel.cpp | 122 | ||||
-rw-r--r-- | src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedOnlyRhsKernel.h | 1 |
2 files changed, 99 insertions, 24 deletions
diff --git a/src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedOnlyRhsKernel.cpp b/src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedOnlyRhsKernel.cpp index 546a61e264..a8bcf8d6a1 100644 --- a/src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedOnlyRhsKernel.cpp +++ b/src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedOnlyRhsKernel.cpp @@ -83,7 +83,6 @@ Status validate_arguments(const ITensorInfo *src0, const ITensorInfo *src1, cons && (!gemm_info.broadcast_bias), "Bias addition only supported with broadcast mode in case the input or dst has to be reinterpreted as 3D"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.fp_mixed_precision, "Mixed precision not supported"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.has_pad_y, "Tensors cannot have padding along the Y direction"); ARM_COMPUTE_RETURN_ON_ERROR(gemm::validate_image2d_support_on_rhs(*src1, rhs_info)); ARM_COMPUTE_RETURN_ERROR_ON_MSG(!post_op_utils.is_post_op_sequence_supported(gemm_info.post_ops), "The sequence of Post Ops is not supported"); @@ -143,8 +142,17 @@ Window validate_and_configure_window(ITensorInfo *src0, ITensorInfo *src1, ITens ARM_COMPUTE_UNUSED(src0, src1, src2); unsigned int &num_elems_processed_per_iteration_x = num_elements_processed[0]; unsigned int &num_elems_processed_per_iteration_y = num_elements_processed[1]; + bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d; bool reinterpret_output_as_3d = gemm_info.depth_output_gemm3d != 0; + // In case both input and dst have to be reinterpreted as 3D tensors, + // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false. + // This approach should only be used when the input/dst tensors have pad on the y direction + if((reinterpret_input_as_3d == reinterpret_output_as_3d) && gemm_info.has_pad_y) + { + reinterpret_output_as_3d = false; + } + TensorInfo tmp_info(*dst); if(reinterpret_output_as_3d) @@ -192,10 +200,19 @@ void ClGemmMatrixMultiplyReshapedOnlyRhsKernel::configure(const CLCompileContext _use_dummy_work_items = preferred_dummy_work_items_support(CLKernelLibrary::get().get_device()); _add_bias = src2 != nullptr; _export_to_cl_image = rhs_info.export_to_cl_image; + _has_pad_y = gemm_info.has_pad_y; _num_post_op_args = gemm_info.post_ops.total_num_arguments(); auto padding_info = get_padding_info({ src0, src1, src2, dst }); + // In case both input and dst have to be reinterpreted as 3D tensors, + // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false. + if((_reinterpret_input_as_3d == _reinterpret_output_as_3d) && _has_pad_y) + { + _reinterpret_input_as_3d = false; + _reinterpret_output_as_3d = false; + } + // Check if we need to slide the matrix B const unsigned int num_dimensions_src0 = src0->num_dimensions(); _slide_matrix_b = (src1->num_dimensions() >= num_dimensions_src0); @@ -212,6 +229,10 @@ void ClGemmMatrixMultiplyReshapedOnlyRhsKernel::configure(const CLCompileContext // This means that the actual m used by the kernel is given by dst->dimension(1) and not by gemm_info.m const unsigned int internal_m = _reinterpret_output_as_3d ? gemm_info.m : dst->dimension(1); + // These variables are used only if gemm_info.has_pad_y == true + const unsigned int h_gemm_3d = _reinterpret_output_as_3d ? dst->dimension(1) : src0->dimension(1); + const unsigned int d_gemm_3d = _reinterpret_output_as_3d ? dst->dimension(2) : src0->dimension(2); + // Shrink M0 to be always <= M (internal_m) to prevent out-of-bounds reads. // NOTE: This might have implications on heuristics and performance const unsigned int internal_m0 = std::min(internal_m, lhs_info.m0); @@ -222,26 +243,31 @@ void ClGemmMatrixMultiplyReshapedOnlyRhsKernel::configure(const CLCompileContext _m = internal_m; _n = gemm_info.n; _k = gemm_info.k; - // Create build options CLBuildOptions build_opts; build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(src0->data_type())); - build_opts.add_option("-DM0=" + support::cpp11::to_string(internal_m0)); - build_opts.add_option("-DN0=" + support::cpp11::to_string(rhs_info.n0)); - build_opts.add_option("-DK0=" + support::cpp11::to_string(rhs_info.k0)); - build_opts.add_option("-DH0=" + support::cpp11::to_string(rhs_info.h0)); - build_opts.add_option("-DPARTIAL_STORE_M0=" + support::cpp11::to_string(partial_store_m0)); - build_opts.add_option("-DPARTIAL_STORE_N0=" + support::cpp11::to_string(partial_store_n0)); - build_opts.add_option_if(_use_dummy_work_items, "-DDUMMY_WORK_ITEMS"); build_opts.add_option_if(!(helpers::float_ops::is_one(alpha)), "-DALPHA=" + float_to_string_with_full_precision(alpha)); build_opts.add_option_if(src2 != nullptr, "-DBETA=" + float_to_string_with_full_precision(beta)); build_opts.add_option_if(helpers::float_ops::is_one(beta), "-DUNIT_BETA"); build_opts.add_option_if(gemm_info.broadcast_bias, "-DBROADCAST_BIAS"); build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(src1->dimension(2))); build_opts.add_option_if(rhs_info.interleave, "-DRHS_INTERLEAVE"); - build_opts.add_option_if(gemm_info.k % rhs_info.k0, "-DRUN_LEFTOVER_K0"); - build_opts.add_option_if((gemm_info.k % rhs_info.k0) && rhs_info.transpose, "-DPARTIAL_K=" + support::cpp11::to_string(gemm_info.k % rhs_info.k0)); - + build_opts.add_option_if(_use_dummy_work_items, "-DDUMMY_WORK_ITEMS"); + build_opts.add_option_if(rhs_info.export_to_cl_image, "-DOPENCL_IMAGE_SUPPORT"); + build_opts.add_option("-DRHS_HEIGHT=" + support::cpp11::to_string(src1->dimension(1))); + build_opts.add_option("-DM0=" + support::cpp11::to_string(internal_m0)); + build_opts.add_option("-DN0=" + support::cpp11::to_string(rhs_info.n0)); + build_opts.add_option("-DK0=" + support::cpp11::to_string(rhs_info.k0)); + build_opts.add_option("-DH0=" + support::cpp11::to_string(rhs_info.h0)); + build_opts.add_option("-DPARTIAL_STORE_M0=" + support::cpp11::to_string(partial_store_m0)); + build_opts.add_option("-DPARTIAL_STORE_N0=" + support::cpp11::to_string(partial_store_n0)); + if(_has_pad_y) + { + build_opts.add_option_if(_reinterpret_input_as_3d, "-DREINTERPRET_INPUT_AS_3D"); + build_opts.add_option_if(_reinterpret_output_as_3d, "-DREINTERPRET_OUTPUT_AS_3D"); + build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(h_gemm_3d)); + build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(d_gemm_3d)); + } // If post_ops are used, then we disable the use of gemm_info.activation_info if(gemm_info.post_ops.size() > 0) { @@ -249,15 +275,15 @@ void ClGemmMatrixMultiplyReshapedOnlyRhsKernel::configure(const CLCompileContext } else { - build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DPOST_OP1"); - build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DP1_ACTIVATION_TYPE=" + lower_string(string_from_activation_func(gemm_info.activation_info.activation()))); - build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DP1_ACTIVATION_A_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.a())); - build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DP1_ACTIVATION_B_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.b())); + build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(gemm_info.activation_info.activation()))); + build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.a())); + build_opts.add_option_if(gemm_info.activation_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(gemm_info.activation_info.b())); } std::string kernel_name("gemm_mm_reshaped_only_rhs_"); kernel_name += rhs_info.transpose ? "t" : "nt"; - kernel_name += _export_to_cl_image ? "_texture" : ""; + kernel_name += rhs_info.export_to_cl_image ? "_texture" : ""; + post_op_utils.set_post_ops_cl_kernel_name(kernel_name, gemm_info.post_ops); // A macro guard to compile ONLY the kernel of interest build_opts.add_option("-D" + upper_string(kernel_name)); @@ -268,8 +294,11 @@ void ClGemmMatrixMultiplyReshapedOnlyRhsKernel::configure(const CLCompileContext // Set config_id for enabling LWS tuning _config_id = kernel_name; _config_id += "_"; + _config_id += (_has_pad_y ? "" : "no_pad_y_"); _config_id += (_add_bias ? "add_bias_" : ""); _config_id += (gemm_info.broadcast_bias ? "broadcast_bias_" : ""); + _config_id += (_reinterpret_input_as_3d ? "3di_" : ""); + _config_id += (_reinterpret_output_as_3d ? "3do_" : ""); _config_id += (gemm_info.activation_info.enabled() ? "fused_activation_" : ""); _config_id += lower_string(string_from_data_type(src0->data_type())); _config_id += "_"; @@ -321,12 +350,24 @@ void ClGemmMatrixMultiplyReshapedOnlyRhsKernel::run_op(ITensorPack &tensors, con ARM_COMPUTE_ERROR_ON(src1->info()->strides_in_bytes()[3] != 0); } + const size_t lhs_idx_batch_size = _reinterpret_input_as_3d && !_has_pad_y ? 3u : 2u; + const size_t rhs_idx_batch_size = 2u; + const size_t bia_idx_batch_size = 2u; + const size_t out_idx_batch_size = _reinterpret_output_as_3d && !_has_pad_y ? 3u : 2u; + Window slice = window.first_slice_window_3D(); Window slice_matrix_b = slice; slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1)); slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1)); + // Get cross plane pads + const unsigned int total_cross_plane_pad_lhs = src0->info()->padding().top + src0->info()->padding().bottom; + const unsigned int total_cross_plane_pad_out = dst->info()->padding().top + dst->info()->padding().bottom; + + // The execution should fail if we try to run with has_pad_y = false but we have padding in either the LHS or DST tensor + ARM_COMPUTE_ERROR_ON(!_has_pad_y && ((total_cross_plane_pad_lhs != 0) || (total_cross_plane_pad_out != 0))); + cl::Image2D src1_image2d; if(_export_to_cl_image) @@ -350,30 +391,63 @@ void ClGemmMatrixMultiplyReshapedOnlyRhsKernel::run_op(ITensorPack &tensors, con unsigned int idx = 0; // LHS buffer - add_3d_tensor_nhw_argument(idx, src0); + add_2D_tensor_argument(idx, src0, slice); // RHS buffer or RHS OpenCL image (_export_to_cl_image == true) if(_export_to_cl_image) { _kernel.setArg(idx++, src1_image2d); } - add_3d_tensor_nhw_argument(idx, src1); + else + { + add_2D_tensor_argument(idx, src1, slice_b); + } // Bias buffer (_add_bias == true) + add_2D_tensor_argument_if(_add_bias, idx, src2, slice); + + // dst buffer + add_2D_tensor_argument(idx, dst, slice); + + // post op argument buffers + for(size_t i = 0; i < _num_post_op_args; ++i) + { + const auto post_op_arg = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(experimental::get_post_op_arg_type(i))); + add_2D_tensor_argument(idx, post_op_arg, slice); + } + + // LHS stride_z + _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(src0->info()->strides_in_bytes()[lhs_idx_batch_size])); + + // RHS stride_z (not used if _export_to_cl_image == true) + _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(src1->info()->strides_in_bytes()[rhs_idx_batch_size])); + + // Bias stride_z (if _add_bias == true) if(_add_bias) { - add_3d_tensor_nhw_argument(idx, src2); + _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(src2->info()->strides_in_bytes()[bia_idx_batch_size])); } - // post op argument buffers + // dst stride_z + _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(dst->info()->strides_in_bytes()[out_idx_batch_size])); + // post op argument stride_z for(size_t i = 0; i < _num_post_op_args; ++i) { const auto post_op_arg = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(experimental::get_post_op_arg_type(i))); - add_3d_tensor_nhw_argument(idx, post_op_arg); + _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(post_op_arg->info()->strides_in_bytes()[2])); } - // dst buffer - add_3d_tensor_nhw_argument(idx, dst); + // Cross-plan padding (if _reinterpret_input_as_3d = true) + if(_reinterpret_input_as_3d && _has_pad_y) + { + _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(total_cross_plane_pad_lhs)); + } + + // Cross-plan padding (if reinterpret_output_as_3d = true) + if(_reinterpret_output_as_3d && _has_pad_y) + { + _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(total_cross_plane_pad_out)); + } // Pass m, n and k at runtime as signed ints, to ensure results of any subractions they could be operand in, would still be signed. _kernel.setArg<cl_int>(idx++, _m); diff --git a/src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedOnlyRhsKernel.h b/src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedOnlyRhsKernel.h index 297e681895..00cdb299ce 100644 --- a/src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedOnlyRhsKernel.h +++ b/src/gpu/cl/kernels/ClGemmMatrixMultiplyReshapedOnlyRhsKernel.h @@ -96,6 +96,7 @@ private: bool _use_dummy_work_items{ false }; bool _add_bias{ false }; bool _export_to_cl_image{ false }; + bool _has_pad_y{ false }; signed int _m{ 1 }; signed int _n{ 1 }; signed int _k{ 1 }; |