Move CPU/GPU files from Core/Runtime to the respective backend folders
Legacy structure contained two libraries core/runtime with two backends
in each.
We reduce the core/runtime libraries to a single library thus merging
the backend files
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I69545765fe7a730368105cdbd067d3135ec7a174
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6155
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultConfigReshapedRhsOnlyValhall.cpp b/src/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultConfigReshapedRhsOnlyValhall.cpp
new file mode 100644
index 0000000..a82084a
--- /dev/null
+++ b/src/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultConfigReshapedRhsOnlyValhall.cpp
@@ -0,0 +1,570 @@
+/*
+ * Copyright (c) 2020-2021 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.
+ */
+#include "src/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultConfigReshapedRhsOnlyValhall.h"
+
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/CLKernelLibrary.h"
+#include "arm_compute/core/GPUTarget.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "src/gpu/cl/kernels/gemm/ClGemmHelpers.h"
+
+#include <utility>
+
+namespace arm_compute
+{
+namespace opencl
+{
+namespace kernels
+{
+namespace gemm
+{
+using namespace arm_compute::misc::shape_calculator;
+
+ClGemmDefaultConfigReshapedRhsOnlyValhall::ClGemmDefaultConfigReshapedRhsOnlyValhall(GPUTarget gpu)
+ : IClGemmKernelConfig(gpu)
+{
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure(unsigned int m, unsigned int n, unsigned int k, unsigned int b, DataType data_type)
+{
+ using ConfigurationFunctionExecutorPtr = std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> (ClGemmDefaultConfigReshapedRhsOnlyValhall::*)(unsigned int m, unsigned int n, unsigned int k,
+ unsigned int b);
+
+ CLGEMMConfigArray<ConfigurationFunctionExecutorPtr> configs_G77(&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_f32,
+ &ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_f16,
+ &ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_u8);
+
+ CLGEMMConfigArray<ConfigurationFunctionExecutorPtr> configs_G78(&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G78_f32,
+ &ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G78_f16,
+ &ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_u8);
+
+ ConfigurationFunctionExecutorPtr func = nullptr;
+
+ switch(_target)
+ {
+ case GPUTarget::G78:
+ func = configs_G78.get_function(data_type);
+ break;
+ case GPUTarget::G77:
+ default:
+ func = configs_G77.get_function(data_type);
+ break;
+ }
+
+ ARM_COMPUTE_ERROR_ON_MSG(func == nullptr, "Data type not support for GEMM");
+ return (this->*func)(m, n, k, b);
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_f32(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
+{
+ if(m == 1)
+ {
+ const float r_mn = static_cast<float>(m) / static_cast<float>(n);
+ const float r_mk = static_cast<float>(m) / static_cast<float>(k);
+
+ if(r_mk <= 0.0064484127797186375)
+ {
+ if(r_mn <= 0.0028273810748942196)
+ {
+ GEMMLHSMatrixInfo lhs_info_buf;
+ GEMMRHSMatrixInfo rhs_info_buf;
+ GEMMLHSMatrixInfo lhs_info_img;
+ GEMMRHSMatrixInfo rhs_info_img;
+
+ const unsigned int h0 = std::max(n / 4, 1U);
+ std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 1, 4, 8, 1, 16, 0, 1, 0, 0, 1);
+ std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 1, 4, 4, 1, h0, 0, 1, 0, 1, 0);
+
+ return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img),
+ std::make_pair(lhs_info_buf, rhs_info_buf),
+ n, k, b, DataType::F32);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 8, 0, 1, 0, 0, 0);
+ }
+ }
+ else
+ {
+ if(r_mk <= 0.020312500186264515)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 4, 0, 1, 0, 0, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 4, 16, 1, 16, 0, 1, 0, 1, 0);
+ }
+ }
+ }
+ else
+ {
+ const float r_mn = static_cast<float>(m) / static_cast<float>(n);
+ const float workload = (static_cast<float>(m) * static_cast<float>(n) * static_cast<float>(b)) / 20.0f;
+ const float r_mk = static_cast<float>(m) / static_cast<float>(k);
+
+ if(workload <= 1999.2000122070312)
+ {
+ if(workload <= 747.1999816894531)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, 0, 1, 0, 1, 0);
+ }
+ else
+ {
+ GEMMLHSMatrixInfo lhs_info_buf;
+ GEMMRHSMatrixInfo rhs_info_buf;
+ GEMMLHSMatrixInfo lhs_info_img;
+ GEMMRHSMatrixInfo rhs_info_img;
+ std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 2, 0, 0, 0, 1, 1);
+ std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, 0, 1, 0, 1, 0);
+
+ return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img),
+ std::make_pair(lhs_info_buf, rhs_info_buf),
+ n, k, b, DataType::F32);
+ }
+ }
+ else
+ {
+ if(r_mn <= 0.03348214365541935)
+ {
+ if(r_mk <= 0.028125000186264515)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, 0, 1, 0, 1, 0);
+ }
+ else
+ {
+ GEMMLHSMatrixInfo lhs_info_buf;
+ GEMMRHSMatrixInfo rhs_info_buf;
+ GEMMLHSMatrixInfo lhs_info_img;
+ GEMMRHSMatrixInfo rhs_info_img;
+ std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 2, 0, 0, 0, 1, 1);
+ std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, 0, 1, 0, 1, 0);
+
+ return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img),
+ std::make_pair(lhs_info_buf, rhs_info_buf),
+ n, k, b, DataType::F32);
+ }
+ }
+ else
+ {
+ GEMMLHSMatrixInfo lhs_info_buf;
+ GEMMRHSMatrixInfo rhs_info_buf;
+ GEMMLHSMatrixInfo lhs_info_img;
+ GEMMRHSMatrixInfo rhs_info_img;
+ std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 2, 0, 1, 0, 0, 1);
+ std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 16, 0, 1, 0, 1, 0);
+
+ return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img),
+ std::make_pair(lhs_info_buf, rhs_info_buf),
+ n, k, b, DataType::F32);
+ }
+ }
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_f16(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
+{
+ ARM_COMPUTE_UNUSED(k);
+ ARM_COMPUTE_UNUSED(b);
+
+ if(m == 1)
+ {
+ const unsigned int h0 = std::max(n / 2, 1U);
+ if(n <= 836.0)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, h0, 0, 1, 0, 1, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, h0, 0, 1, 0, 1, 0);
+ }
+ }
+ else if(m < 128)
+ {
+ const int h0 = std::max(std::min(static_cast<int>(n / 4), static_cast<int>(256)), static_cast<int>(1));
+ if(k >= 512)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 4, 16, 1, h0, 0, 1, 0, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, h0, 0, 1, 0, 0);
+ }
+ }
+ else
+ {
+ const int h0 = std::max(std::min(static_cast<int>(n / 4), static_cast<int>(256)), static_cast<int>(1));
+ if(n >= 64)
+ {
+ return configure_lhs_rhs_info(m, n, 4, 8, 4, 1, h0, 0, 1, 0, 0);
+ }
+ else
+ {
+ if(k >= 512)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 4, 16, 1, h0, 0, 1, 0, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, h0, 0, 1, 0, 0);
+ }
+ }
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_u8(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
+{
+ ARM_COMPUTE_UNUSED(k);
+ ARM_COMPUTE_UNUSED(b);
+
+ if(m == 1)
+ {
+ const unsigned int h0 = std::max(n / 2, 1U);
+ return configure_lhs_rhs_info(m, n, 1, 4, 16, 1, h0, 0, 1, 0, 1);
+ }
+ else
+ {
+ const int h0 = std::max(std::min(static_cast<int>(n / 4), static_cast<int>(256)), static_cast<int>(1));
+ if(m >= 28)
+ {
+ return configure_lhs_rhs_info(m, n, 4, 4, 16, 1, h0, 0, 1, 0, 1);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 2, 4, 16, 1, h0, 0, 1, 0, 1);
+ }
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G78_f32(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
+{
+ const float r_mn = static_cast<float>(m) / static_cast<float>(n);
+ const float r_mk = static_cast<float>(m) / static_cast<float>(k);
+ const float r_nk = static_cast<float>(n) / static_cast<float>(k);
+ const float workload = (static_cast<float>(m) * static_cast<float>(n) * static_cast<float>(b)) / 20.0f;
+
+ if(m == 1)
+ {
+ if(workload <= 278.7000f)
+ {
+ if(workload <= 7.5000f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0);
+ }
+ else
+ {
+ if(r_mn <= 0.0031f)
+ {
+ if(workload <= 256.6000f)
+ {
+ if(workload <= 16.7500f)
+ {
+ if(r_nk <= 1.6671f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0);
+ }
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0);
+ }
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0);
+ }
+ }
+ else
+ {
+ if(r_mk <= 0.0027f)
+ {
+ if(r_mk <= 0.0014f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0);
+ }
+ else
+ {
+ if(workload <= 8.9500f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0);
+ }
+ }
+ }
+ else
+ {
+ if(workload <= 14.1500f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0);
+ }
+ else
+ {
+ if(r_mk <= 0.0041f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0);
+ }
+ }
+ }
+ }
+ }
+ }
+ else
+ {
+ if(workload <= 363.7000f)
+ {
+ if(r_mk <= 0.0031f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 4, 2, 1, 32, 0, 1, 0, 1, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 4, 4, 1, 32, 0, 1, 0, 1, 0);
+ }
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 4, 2, 1, 32, 0, 1, 0, 1, 0);
+ }
+ }
+ }
+ else
+ {
+ if(workload <= 1384.8000f)
+ {
+ if(workload <= 704.0000f)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 32, 0, 1, 0, 1, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 4, 0, 0, 0, 1, 1);
+ }
+ }
+ else
+ {
+ if(workload <= 16761.6006f)
+ {
+ if(r_mn <= 187.1250f)
+ {
+ return configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 16, 0, 0, 0, 1, 1);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 4, 0, 0, 0, 1, 1);
+ }
+ }
+ else
+ {
+ if(r_mk <= 432.4630f)
+ {
+ return configure_lhs_rhs_info(m, n, 5, 4, 4, 1, 16, 0, 0, 0, 1, 1);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 2, 4, 4, 1, 16, 0, 1, 0, 1, 1);
+ }
+ }
+ }
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G78_f16(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
+{
+ const float r_mn = static_cast<float>(m) / static_cast<float>(n);
+ const float r_mk = static_cast<float>(m) / static_cast<float>(k);
+ const float r_nk = static_cast<float>(n) / static_cast<float>(k);
+ const float workload = (static_cast<float>(m) * static_cast<float>(n) * static_cast<float>(b)) / 20.0f;
+
+ if(m == 1)
+ {
+ if(r_mn <= 0.0038f)
+ {
+ if(workload <= 353.9000f)
+ {
+ if(workload <= 278.7000f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 4, 1, 32, 0, 0, 1, 0, 0);
+ }
+ else
+ {
+ if(r_mk <= 0.0004f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 4, 1, 32, 0, 0, 1, 0, 0);
+ }
+ else
+ {
+ if(r_mk <= 0.0030f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 8, 4, 1, 8, 0, 1, 1, 0, 1);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 4, 1, 32, 0, 0, 1, 0, 0);
+ }
+ }
+ }
+ }
+ else
+ {
+ if(r_nk <= 1.9384f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 4, 1, 32, 0, 0, 1, 0, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 8, 4, 1, 8, 0, 1, 1, 0, 1);
+ }
+ }
+ }
+ else
+ {
+ if(r_nk <= 1.0368f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 32, 0, 0, 1, 0, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 4, 1, 32, 0, 0, 1, 0, 0);
+ }
+ }
+ }
+ else
+ {
+ if(workload <= 1422.4000f)
+ {
+ if(workload <= 704.0000f)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 2, 8, 1, 32, 0, 0, 1, 0, 0);
+ }
+ else
+ {
+ if(workload <= 1197.6000f)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 8, 0, 1, 1, 0, 1);
+ }
+ else
+ {
+ if(workload <= 1241.6000f)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 8, 8, 1, 16, 0, 1, 1, 0, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 8, 0, 1, 1, 0, 1);
+ }
+ }
+ }
+ }
+ else
+ {
+ if(workload <= 2769.6000f)
+ {
+ if(workload <= 1846.4000f)
+ {
+ if(r_mn <= 2.4927f)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 8, 8, 1, 16, 0, 1, 1, 0, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 32, 0, 1, 1, 0, 0);
+ }
+ }
+ else
+ {
+ if(r_mn <= 0.6261f)
+ {
+ return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 32, 0, 1, 1, 0, 0);
+ }
+ else
+ {
+ if(r_mk <= 3.4453f)
+ {
+ if(r_mn <= 1.4135f)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 8, 8, 1, 16, 0, 1, 1, 0, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 32, 0, 1, 1, 0, 0);
+ }
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 2, 8, 8, 1, 16, 0, 1, 1, 0, 0);
+ }
+ }
+ }
+ }
+ else
+ {
+ if(r_nk <= 0.0302f)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 8, 0, 1, 1, 0, 1);
+ }
+ else
+ {
+ if(r_mk <= 181.3750f)
+ {
+ return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 32, 0, 1, 1, 0, 0);
+ }
+ else
+ {
+ if(workload <= 28035.2002f)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 8, 8, 1, 16, 0, 1, 1, 0, 0);
+ }
+ else
+ {
+ if(r_mk <= 808.6667f)
+ {
+ return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 32, 0, 1, 1, 0, 0);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 2, 8, 8, 1, 16, 0, 1, 1, 0, 0);
+ }
+ }
+ }
+ }
+ }
+ }
+ }
+}
+} // namespace gemm
+} // namespace kernels
+} // namespace opencl
+} // namespace arm_compute