/* * Copyright (c) 2022 Arm Limited. * * SPDX-License-Identifier: MIT * * 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. */ #if defined(ENABLE_EXPERIMENTAL_DYNAMIC_FUSION) #include "src/core/experimental/dynamic_fusion/ClKernelBuildingImpl/components/ClGemmNativeKernelComponent.h" namespace arm_compute { namespace experimental { namespace dynamic_fusion { ComponentType ClGemmNativeKernelComponent::get_component_type() const { return ComponentType::Complex; } std::set ClGemmNativeKernelComponent::get_headers_list() const { return std::set { "./common/experimental/gemm_fused_post_ops/act_eltwise_op_act/fp_post_ops_act_eltwise_op_act.h", "gemm_helpers.h", "repeat.h" }; } std::string ClGemmNativeKernelComponent::get_additional_macros() const { return R"_( #define VFMA(a, b, c) \ ({ \ c = fma(a, b, c); \ }) #if M0 == 1 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ }) #elif M0 == 2 // M0 == 2 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ }) #elif M0 == 3 // M0 == 3 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ }) #elif M0 == 4 // M0 == 4 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ }) #elif M0 == 5 // M0 == 5 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \ }) #elif M0 == 6 // M0 == 6 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \ }) #elif M0 == 7 // M0 == 7 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##6).s##i), b, (c##6)); \ }) #elif M0 == 8 // M0 == 8 #define RHS_VFMA_M0xN0(i, a, b, c) \ ({ \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##0).s##i), b, (c##0)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##1).s##i), b, (c##1)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##2).s##i), b, (c##2)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##3).s##i), b, (c##3)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##4).s##i), b, (c##4)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##5).s##i), b, (c##5)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##6).s##i), b, (c##6)); \ VFMA((VEC_DATA_TYPE(DATA_TYPE, N0))((a##7).s##i), b, (c##7)); \ }) #else // M0 not supported #error "M0 not supported" #endif // M0 not supported )_"; } std::string ClGemmNativeKernelComponent::get_component_code() const { std::string code = R"_( //------------------ START KERNEL {{meta_kernel_id}} --------------------- // IN_0(lhs) {{lhs}} // IN_1(rhs) {{rhs}} )_"; if(!_bias.is_empty()) { code += R"_( // IN_2(bias) {{bias}} )_"; } code += R"_( // OUT(dst, accum) {{dst}} // Initialize the accumulators REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(DATA_TYPE, N0), {{dst}}, 0); //VEC_DATA_TYPE(DATA_TYPE, N0) c0=0,c1=0,c2=0,... c(M0-1)=0; { #if defined(DUMMY_WORK_ITEMS) if((g_x * N0 >= N) || (g_y * M0 >= M)) { return; } #endif // defined(DUMMY_WORK_ITEMS) // Compute LHS matrix address uint lhs_offset = {{lhs}}_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(g_y, M0, PARTIAL_STORE_M0) * (uint){{lhs}}_stride_y; // Compute RHS matrix address uint rhs_offset = {{rhs}}_offset_first_element_in_bytes + g_x * N0 * sizeof(DATA_TYPE); #if defined(MATRIX_B_DEPTH) // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 rhs_offset += (g_z % MATRIX_B_DEPTH) * {{rhs}}_stride_z; #else // defined(MATRIX_B_DEPTH) rhs_offset += g_z * {{rhs}}_stride_z; #endif // defined(MATRIX_B_DEPTH) REPEAT_VAR_INIT_TO_CONST(M0, uint, zlhs, 0); #if defined(REINTERPRET_INPUT_AS_3D) // The plane (zlhs) is calculated dividing M (g_y * M0) by HEIGHT_GEMM3D CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(g_y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, {{lhs}}_cross_plane_pad, {{lhs}}_stride_y); // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we // multiply lhs_stride_z by DEPTH_GEMM3D lhs_offset += g_z * {{lhs}}_stride_z * DEPTH_GEMM3D; #else // defined(REINTERPRET_INPUT_AS_3D) // Add offset for batched GEMM lhs_offset += g_z * {{lhs}}_stride_z; #endif // defined(REINTERPRET_INPUT_AS_3D) int i = 0; #if K0 > 1 for(; i <= (K - K0); i += K0) { // Supported cases (M0, K0): // 1,2 - 1,3 - 1,4 - 1,8 - 1,16 // 2,2 - 2,3 - 2,4 - 2,8 - 2,16 // 3,2 - 3,3 - 3,4 - 3,8 - 3,16 // 4,2 - 4,3 - 4,4 - 4,8 - 4,16 // 5,2 - 5,3 - 5,4 - 5,8 - 5,16 // 6,2 - 6,3 - 6,4 - 6,8 - 6,16 // 7,2 - 7,3 - 7,4 - 7,8 - 7,16 // 8,2 - 8,3 - 8,4 - 8,8 - 8,16 // Load values from LHS matrix LOAD_BLOCK(M0, K0, DATA_TYPE, a, {{lhs}}_ptr, lhs_offset, {{lhs}}_stride_y, zlhs); // Load values from RHS matrix LOAD_BLOCK(K0, N0, DATA_TYPE, b, {{rhs}}_ptr, rhs_offset, {{rhs}}_stride_y, g_zero); RHS_VFMA_M0xN0(0, a, b0, {{dst}}); RHS_VFMA_M0xN0(1, a, b1, {{dst}}); #if K0 > 2 RHS_VFMA_M0xN0(2, a, b2, {{dst}}); #endif // K0 > 2 #if K0 > 3 RHS_VFMA_M0xN0(3, a, b3, {{dst}}); #endif // K0 > 3 #if K0 > 4 RHS_VFMA_M0xN0(4, a, b4, {{dst}}); RHS_VFMA_M0xN0(5, a, b5, {{dst}}); RHS_VFMA_M0xN0(6, a, b6, {{dst}}); RHS_VFMA_M0xN0(7, a, b7, {{dst}}); #endif // K0 > 4 #if K0 > 8 RHS_VFMA_M0xN0(8, a, b8, {{dst}}); RHS_VFMA_M0xN0(9, a, b9, {{dst}}); RHS_VFMA_M0xN0(A, a, bA, {{dst}}); RHS_VFMA_M0xN0(B, a, bB, {{dst}}); RHS_VFMA_M0xN0(C, a, bC, {{dst}}); RHS_VFMA_M0xN0(D, a, bD, {{dst}}); RHS_VFMA_M0xN0(E, a, bE, {{dst}}); RHS_VFMA_M0xN0(F, a, bF, {{dst}}); #endif // K0 > 8 lhs_offset += K0 * sizeof(DATA_TYPE); rhs_offset += K0 * {{rhs}}_stride_y; } #endif // K0 > 1 // Left-over accumulations for(; i < K; ++i) { // Load values from LHS matrix VEC_DATA_TYPE(DATA_TYPE, 2) a0 = *((__global DATA_TYPE *)({{lhs}}_ptr + lhs_offset + 0 * {{lhs}}_stride_y + zlhs0)); #if M0 > 1 VEC_DATA_TYPE(DATA_TYPE, 2) a1 = *((__global DATA_TYPE *)({{lhs}}_ptr + lhs_offset + 1 * {{lhs}}_stride_y + zlhs1)); #endif // M0 > 1 #if M0 > 2 VEC_DATA_TYPE(DATA_TYPE, 2) a2 = *((__global DATA_TYPE *)({{lhs}}_ptr + lhs_offset + 2 * {{lhs}}_stride_y + zlhs2)); #endif // M0 > 2 #if M0 > 3 VEC_DATA_TYPE(DATA_TYPE, 2) a3 = *((__global DATA_TYPE *)({{lhs}}_ptr + lhs_offset + 3 * {{lhs}}_stride_y + zlhs3)); #endif // M0 > 3 #if M0 > 4 VEC_DATA_TYPE(DATA_TYPE, 2) a4 = *((__global DATA_TYPE *)({{lhs}}_ptr + lhs_offset + 4 * {{lhs}}_stride_y + zlhs4)); #endif // M0 > 4 #if M0 > 5 VEC_DATA_TYPE(DATA_TYPE, 2) a5 = *((__global DATA_TYPE *)({{lhs}}_ptr + lhs_offset + 5 * {{lhs}}_stride_y + zlhs5)); #endif // M0 > 5 #if M0 > 6 VEC_DATA_TYPE(DATA_TYPE, 2) a6 = *((__global DATA_TYPE *)({{lhs}}_ptr + lhs_offset + 6 * {{lhs}}_stride_y + zlhs6)); #endif // M0 > 6 #if M0 > 7 VEC_DATA_TYPE(DATA_TYPE, 2) a7 = *((__global DATA_TYPE *)({{lhs}}_ptr + lhs_offset + 7 * {{lhs}}_stride_y + zlhs7)); #endif // M0 > 7 VEC_DATA_TYPE(DATA_TYPE, N0) b = VLOAD(N0)(0, (__global DATA_TYPE *)({{rhs}}_ptr + rhs_offset + 0 * {{rhs}}_stride_y)); RHS_VFMA_M0xN0(0, a, b, {{dst}}); lhs_offset += sizeof(DATA_TYPE); rhs_offset += {{rhs}}_stride_y; } // Multiply by the weight of matrix-matrix product and store the result #if defined(ALPHA) SCALE_BLOCK(M0, DATA_TYPE, {{dst}}, ALPHA); #endif // defined(ALPHA) )_"; if(!_bias.is_empty()) { code += R"_( // Add beta*bias #if defined(BROADCAST_BIAS) __global uchar *bias_addr = {{bias}}_ptr + {{bias}}_offset_first_element_in_bytes + (get_global_id(0) * (uint)N0 * sizeof(DATA_TYPE)); LOAD_BLOCK(1, N0, DATA_TYPE, bias, bias_addr, 0, {{bias}}_stride_y, g_zero); #ifndef UNIT_BETA SCALE_BLOCK(1, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias[broadcasted] ADD_BLOCK_BROADCAST(M0, {{dst}}, bias0); #else // defined(BROADCAST_BIAS) __global uchar *bias_addr = {{bias}}_ptr + {{bias}}_offset_first_element_in_bytes + (g_x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(g_y, M0, PARTIAL_STORE_M0) * {{bias}}_stride_y) + g_z * {{bias}}_stride_z; LOAD_BLOCK(M0, N0, DATA_TYPE, bias, bias_addr, 0, {{bias}}_stride_y, g_zero); #ifndef UNIT_BETA SCALE_BLOCK(M0, DATA_TYPE, bias, BETA); #endif // UNIT_BIAS // c = c + bias ADD_BLOCK(M0, {{dst}}, bias); #endif // defined(BROADCAST_BIAS) )_"; } code += R"_( } //------------------ END KERNEL {{meta_kernel_id}} --------------------- )_"; return code.c_str(); } ClGemmNativeKernelComponent::TagLUT ClGemmNativeKernelComponent::allocate_vars(SharedVarTable &vtable) const { TagLUT lut{}; lut["meta_kernel_id"] = id(); lut["lhs"] = vtable.add(_lhs, ClKernelArgRuntimeDescriptor(_lhs.arg_id, TensorArgType::Image_3D), "lhs"); lut["rhs"] = vtable.add(_rhs, ClKernelArgRuntimeDescriptor(_rhs.arg_id, TensorArgType::Image_3D), "rhs"); if(!_bias.is_empty()) // optional bias { lut["bias"] = vtable.add(_bias, ClKernelArgRuntimeDescriptor(_bias.arg_id, TensorArgType::Image_3D), "bias"); } lut["dst"] = vtable.add(_dst, ClKernelArgRuntimeDescriptor(_dst.arg_id, TensorArgType::Image_3D), "dst"); return lut; } } // namespace dynamic_fusion } // namespace experimental } // namespace arm_compute #endif // defined(ENABLE_EXPERIMENTAL_DYNAMIC_FUSION)