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diff --git a/src/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultConfigReshapedRhsOnlyBifrost.cpp b/src/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultConfigReshapedRhsOnlyBifrost.cpp
new file mode 100644
index 0000000000..c4825bfbeb
--- /dev/null
+++ b/src/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultConfigReshapedRhsOnlyBifrost.cpp
@@ -0,0 +1,577 @@
+/*
+ * Copyright (c) 2019-2021 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/ClGemmDefaultConfigReshapedRhsOnlyBifrost.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;
+
+ClGemmDefaultConfigReshapedRhsOnlyBifrost::ClGemmDefaultConfigReshapedRhsOnlyBifrost(GPUTarget gpu)
+ : IClGemmKernelConfig(gpu)
+{
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b, DataType data_type)
+{
+ using ConfigurationFunctionExecutorPtr = std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> (
+ ClGemmDefaultConfigReshapedRhsOnlyBifrost::*)(unsigned int m, unsigned int n, unsigned int k, unsigned int b);
+
+ CLGEMMConfigArray<ConfigurationFunctionExecutorPtr> configs_G51(
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G51_f32,
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G51_f16,
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G51_u8);
+
+ CLGEMMConfigArray<ConfigurationFunctionExecutorPtr> configs_G52(
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G52_f32,
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G52_f16,
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G7x_u8);
+
+ CLGEMMConfigArray<ConfigurationFunctionExecutorPtr> configs_G31(
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G7x_f32,
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G7x_f16,
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G31_u8);
+
+ CLGEMMConfigArray<ConfigurationFunctionExecutorPtr> configs_G76(
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G76_f32,
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G76_f16,
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G76_u8);
+
+ CLGEMMConfigArray<ConfigurationFunctionExecutorPtr> configs_G7x(
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G7x_f32,
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G7x_f16,
+ &ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G7x_u8);
+
+ ConfigurationFunctionExecutorPtr func = nullptr;
+ switch (_target)
+ {
+ case GPUTarget::G76:
+ func = configs_G76.get_function(data_type);
+ break;
+ case GPUTarget::G51:
+ func = configs_G51.get_function(data_type);
+ break;
+ case GPUTarget::G52:
+ func = configs_G52.get_function(data_type);
+ break;
+ case GPUTarget::G31:
+ func = configs_G31.get_function(data_type);
+ break;
+ default:
+ func = configs_G7x.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> ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G7x_f32(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b)
+{
+ ARM_COMPUTE_UNUSED(k);
+ ARM_COMPUTE_UNUSED(b);
+
+ if (m == 1)
+ {
+ if (n <= 2548)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 4, false, true, false, true, false);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 4, 16, 1, 8, false, true, false, true, false);
+ }
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 4, false, true, false, true);
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G31_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, 4, 1, h0, 0, 1, 0, 1);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 4, 4, 4, 1, h0, 0, 1, 0, 1);
+ }
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G76_f32(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b)
+{
+ ARM_COMPUTE_UNUSED(k);
+ ARM_COMPUTE_UNUSED(b);
+
+ GEMMLHSMatrixInfo lhs_info_buf;
+ GEMMRHSMatrixInfo rhs_info_buf;
+ GEMMLHSMatrixInfo lhs_info_img;
+ GEMMRHSMatrixInfo rhs_info_img;
+
+ const bool is_workload_big = ((m * n * b) / 16) >= 2048;
+
+ if (m == 1)
+ {
+ if (n >= 8192)
+ {
+ const unsigned int h0 = std::max(n / 4, 1U);
+ return configure_lhs_rhs_info(m, n, 1, 4, 8, 1, h0, false, true, false, true, false);
+ }
+ else
+ {
+ const unsigned int h0 = std::max(n / 2, 1U);
+ if (n <= 204)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, h0, false, true, false, true, false);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, h0, false, true, false, true, false);
+ }
+ }
+ }
+ else
+ {
+ const int h0 = std::max(std::min(static_cast<int>(n / 4), static_cast<int>(16)), static_cast<int>(1));
+ if (is_workload_big)
+ {
+ std::tie(lhs_info_buf, rhs_info_buf) =
+ configure_lhs_rhs_info(m, n, 4, 4, 4, 1, h0, false, true, false, true);
+ }
+ else
+ {
+ std::tie(lhs_info_buf, rhs_info_buf) =
+ configure_lhs_rhs_info(m, n, 2, 4, 8, 1, h0, false, true, false, true);
+ }
+ }
+
+ // Get lhs_info/rhs_info in case of OpenCL image
+ const int h0 = std::max(std::min(static_cast<int>(n / 4), static_cast<int>(16)), static_cast<int>(1));
+ if (is_workload_big)
+ {
+ std::tie(lhs_info_img, rhs_info_img) =
+ configure_lhs_rhs_info(m, n, 4, 4, 4, 1, h0, false, true, false, false, true);
+ }
+ else
+ {
+ std::tie(lhs_info_img, rhs_info_img) =
+ configure_lhs_rhs_info(m, n, 2, 4, 8, 1, h0, false, true, false, true, true);
+ }
+
+ const TensorInfo tensor_rhs_info(TensorShape(n, k, b), 1, DataType::F32);
+ const TensorShape shape = compute_rhs_reshaped_shape(tensor_rhs_info, rhs_info_img);
+ const TensorInfo tensor_reshaped_info(shape, 1, DataType::F32);
+
+ // In case of vector by matrix or small workloads, we use the OpenCL buffer rather than the OpenCL image2d
+ const bool use_cl_image2d = ((m == 1) || ((((m * n * b) / 16) < 2048) && n < 128)) ? false : true;
+
+ if (bool(validate_image2d_support_on_rhs(tensor_reshaped_info, rhs_info_img)) && use_cl_image2d)
+ {
+ return std::make_pair(lhs_info_img, rhs_info_img);
+ }
+ else
+ {
+ return std::make_pair(lhs_info_buf, rhs_info_buf);
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G52_f32(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b)
+{
+ const float workload = (static_cast<float>(m) * static_cast<float>(n) * static_cast<float>(b)) / 20.0f;
+ const float r_nk = static_cast<float>(n) / static_cast<float>(k);
+
+ GEMMLHSMatrixInfo lhs_info_buf;
+ GEMMRHSMatrixInfo rhs_info_buf;
+ GEMMLHSMatrixInfo lhs_info_img;
+ GEMMRHSMatrixInfo rhs_info_img;
+
+ if (m == 1)
+ {
+ if (r_nk <= 0.4664f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 16, false, true, false, true, false);
+ }
+ else
+ {
+ std::tie(lhs_info_img, rhs_info_img) =
+ configure_lhs_rhs_info(m, n, 1, 4, 8, 1, 16, false, true, false, true, true);
+ std::tie(lhs_info_buf, rhs_info_buf) =
+ configure_lhs_rhs_info(m, n, 1, 4, 8, 1, 16, false, true, false, true, false);
+
+ 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 (workload <= 274.4000f)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 16, false, false, false, true, false);
+ }
+ else
+ {
+ std::tie(lhs_info_img, rhs_info_img) =
+ configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 2, false, false, false, true, true);
+ std::tie(lhs_info_buf, rhs_info_buf) =
+ configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 2, false, false, false, true, false);
+
+ 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> ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G51_f32(
+ 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 n0 = n < 1280 ? 2 : 4;
+ const unsigned int h0 = std::max(n / n0, 1U);
+ return configure_lhs_rhs_info(m, n, 1, n0, 4, 1, h0, false, true, false, true);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 2, false, true, false, true);
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G7x_f16(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b)
+{
+ ARM_COMPUTE_UNUSED(k);
+ ARM_COMPUTE_UNUSED(b);
+
+ if (m == 1)
+ {
+ if (n > 2048)
+ {
+ const unsigned int h0 = std::max(n / 4, 1U);
+ return configure_lhs_rhs_info(m, n, 1, 4, 4, 1, h0, false, true, false, true);
+ }
+ else
+ {
+ const unsigned int h0 = std::max(n / 2, 1U);
+ return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, h0, false, true, false, true);
+ }
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 4, false, true, false, true);
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G52_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 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);
+ const float r_nk = static_cast<float>(n) / static_cast<float>(k);
+
+ GEMMLHSMatrixInfo lhs_info_buf;
+ GEMMRHSMatrixInfo rhs_info_buf;
+ GEMMLHSMatrixInfo lhs_info_img;
+ GEMMRHSMatrixInfo rhs_info_img;
+
+ if (m == 1)
+ {
+ std::tie(lhs_info_buf, rhs_info_buf) =
+ configure_lhs_rhs_info(m, n, 1, 4, 16, 1, 16, false, true, false, false, false);
+
+ if (r_mk <= 0.0026f)
+ {
+ if (r_nk <= 0.4664f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 32, false, true, false, true, false);
+ }
+ else
+ {
+ std::tie(lhs_info_img, rhs_info_img) =
+ configure_lhs_rhs_info(m, n, 1, 4, 16, 1, 16, false, true, false, false, true);
+ 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::F16);
+ }
+ }
+ else
+ {
+ if (r_mk <= 0.0148f)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 32, false, true, false, true, false);
+ }
+ else
+ {
+ std::tie(lhs_info_img, rhs_info_img) =
+ configure_lhs_rhs_info(m, n, 1, 4, 16, 1, 16, false, true, false, false, true);
+ 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::F16);
+ }
+ }
+ }
+ else
+ {
+ std::tie(lhs_info_buf, rhs_info_buf) =
+ configure_lhs_rhs_info(m, n, 5, 8, 4, 1, 2, false, false, false, false, false);
+
+ if (workload <= 362.6000f)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 2, 8, 1, 16, false, false, false, true, false);
+ }
+ else
+ {
+ if (r_mn <= 22.6067f)
+ {
+ if (workload <= 708.8000f)
+ {
+ std::tie(lhs_info_img, rhs_info_img) =
+ configure_lhs_rhs_info(m, n, 5, 4, 4, 1, 2, false, false, false, false, true);
+ 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::F16);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 5, 8, 2, 1, 16, false, false, false, false, false);
+ }
+ }
+ else
+ {
+ if (r_nk <= 0.0917f)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 2, 8, 1, 16, false, false, false, true, false);
+ }
+ else
+ {
+ std::tie(lhs_info_img, rhs_info_img) =
+ configure_lhs_rhs_info(m, n, 5, 4, 4, 1, 2, false, false, false, false, true);
+ 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::F16);
+ }
+ }
+ }
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G76_f16(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b)
+{
+ ARM_COMPUTE_UNUSED(k);
+
+ if (m == 1)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 32, false, true, false, true, false);
+ }
+ 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;
+
+ if (workload <= 7449.60f)
+ {
+ if (workload <= 691.60f)
+ {
+ return configure_lhs_rhs_info(m, n, 2, 2, 8, 1, 8, false, false, false, false, false);
+ }
+ else
+ {
+ if (workload <= 4155.20f)
+ {
+ return configure_lhs_rhs_info(m, n, 5, 2, 8, 1, 16, false, false, false, false, false);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 5, 8, 2, 1, 32, false, false, false, false, false);
+ }
+ }
+ }
+ else
+ {
+ if (workload <= 16300.80f)
+ {
+ if (r_mn <= 44.56f)
+ {
+ 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, 8, 4, 4, 1, 1, false, true, false, false, true);
+ std::tie(lhs_info_buf, rhs_info_buf) =
+ configure_lhs_rhs_info(m, n, 5, 2, 8, 1, 16, false, false, false, false, false);
+
+ 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::F16);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 5, 2, 8, 1, 16, false, false, false, false, false);
+ }
+ }
+ 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, 5, 4, 4, 1, 2, false, true, false, false, true);
+ std::tie(lhs_info_buf, rhs_info_buf) =
+ configure_lhs_rhs_info(m, n, 5, 2, 8, 1, 16, false, false, false, false, false);
+
+ 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::F16);
+ }
+ }
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G51_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 n0 = n < 1280 ? 2 : 4;
+ const unsigned int h0 = std::max(n / n0, 1U);
+ return configure_lhs_rhs_info(m, n, 1, n0, 8, 1, h0, false, true, false, true);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 2, false, true, false, true);
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G7x_u8(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b)
+{
+ ARM_COMPUTE_UNUSED(k);
+ ARM_COMPUTE_UNUSED(b);
+
+ if (dot8_supported(CLKernelLibrary::get().get_device()))
+ {
+ if (m == 1)
+ {
+ const unsigned int h0 = std::max(n / 2, 1U);
+ return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, h0, false, true, false, true);
+ }
+ else
+ {
+ const unsigned int h0 = std::max(n / 4, 1U);
+ return configure_lhs_rhs_info(m, n, 4, 4, 16, 1, h0, false, true, false, true);
+ }
+ }
+ else
+ {
+ const int h0 = std::max(std::min(static_cast<int>(n / 2), static_cast<int>(128)), static_cast<int>(1));
+ if (m == 1)
+ {
+ return configure_lhs_rhs_info(m, n, 1, 2, 4, 1, h0, false, true, false, true);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 4, 2, 16, 1, h0, false, true, false, true);
+ }
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G76_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, 2, 16, 1, h0, false, true, false, true);
+ }
+ else
+ {
+ return configure_lhs_rhs_info(m, n, 4, 4, 16, 1, 2, false, true, false, true);
+ }
+}
+
+std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyBifrost::configure_G51_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, false, true, false, true);
+ }
+ else
+ {
+ const unsigned int h0 = std::max(n / 2, 1U);
+ return configure_lhs_rhs_info(m, n, 4, 2, 16, 1, h0, false, true, false, true);
+ }
+}
+
+} // namespace gemm
+} // namespace kernels
+} // namespace opencl
+} // namespace arm_compute