| /* |
| * 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<std::string> ClGemmNativeKernelComponent::get_headers_list() const |
| { |
| return std::set<std::string> { "./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) |