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diff --git a/src/runtime/heuristics/matmul_native/ClMatMulNativeDefaultConfigValhall.cpp b/src/runtime/heuristics/matmul_native/ClMatMulNativeDefaultConfigValhall.cpp
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+++ b/src/runtime/heuristics/matmul_native/ClMatMulNativeDefaultConfigValhall.cpp
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+/*
+ * Copyright (c) 2023 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/runtime/heuristics/matmul_native/ClMatMulNativeDefaultConfigValhall.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/KernelDescriptors.h"
+#include "arm_compute/core/TensorInfo.h"
+
+#include "src/gpu/cl/kernels/ClMatMulNativeKernel.h"
+#include "src/runtime/heuristics/matmul_native/ClMatMulNativeHelpers.h"
+
+#include <utility>
+
+namespace arm_compute
+{
+namespace cl_matmul
+{
+ClMatMulNativeDefaultConfigValhall::ClMatMulNativeDefaultConfigValhall(GPUTarget gpu) : IClMatMulNativeKernelConfig(gpu)
+{
+}
+
+MatMulKernelInfo
+ClMatMulNativeDefaultConfigValhall::configure(const ITensorInfo *lhs, const ITensorInfo *rhs, const MatMulInfo &info)
+{
+ using ConfigurationFunctionExecutorPtr = MatMulKernelInfo (ClMatMulNativeDefaultConfigValhall::*)(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool rhs_lock_padding, const MatMulInfo &info);
+
+ ClMatMulNativeConfigArray<ConfigurationFunctionExecutorPtr> configs_G710(
+ &ClMatMulNativeDefaultConfigValhall::configure_G710_f32,
+ &ClMatMulNativeDefaultConfigValhall::configure_G710_f16,
+ &ClMatMulNativeDefaultConfigValhall::configure_G710_u8);
+
+ ClMatMulNativeConfigArray<ConfigurationFunctionExecutorPtr> configs_G715(
+ &ClMatMulNativeDefaultConfigValhall::configure_G715_f32,
+ &ClMatMulNativeDefaultConfigValhall::configure_G715_f16,
+ &ClMatMulNativeDefaultConfigValhall::configure_G715_u8);
+
+ ConfigurationFunctionExecutorPtr func = nullptr;
+ switch (_target)
+ {
+ case GPUTarget::G715:
+ case GPUTarget::G615:
+ func = configs_G715.get_function(lhs->data_type());
+ break;
+ case GPUTarget::G710:
+ default:
+ func = configs_G710.get_function(lhs->data_type());
+ break;
+ }
+
+ const bool adj_lhs = info.adj_lhs();
+ const bool adj_rhs = info.adj_rhs();
+
+ TensorShape lhs_shape = lhs->tensor_shape();
+ TensorShape rhs_shape = rhs->tensor_shape();
+
+ const bool is_batched = lhs_shape.num_dimensions() > 2;
+
+ if (is_batched == true)
+ {
+ lhs_shape.collapse_from(2);
+ }
+
+ const unsigned int m = adj_lhs ? lhs_shape.x() : lhs_shape.y();
+ const unsigned int n = adj_rhs ? rhs_shape.y() : rhs_shape.x();
+ const unsigned int k = adj_lhs ? lhs_shape.y() : lhs_shape.x();
+ const unsigned int b = lhs_shape.z();
+
+ ARM_COMPUTE_ERROR_ON_MSG(func == nullptr, "Data type not supported for matmul native");
+ return (this->*func)(m, n, k, b, rhs->lock_paddings(), info);
+}
+
+MatMulKernelInfo ClMatMulNativeDefaultConfigValhall::configure_G715_f32(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool rhs_lock_padding, const MatMulInfo &info)
+{
+ ARM_COMPUTE_UNUSED(m, n, k, b, rhs_lock_padding);
+ return {info.adj_lhs(), info.adj_rhs(), /* m0 */ 1, /* n0 */ 4, /* k0 */ 1, /* export_to_cl_image */ false};
+}
+
+MatMulKernelInfo ClMatMulNativeDefaultConfigValhall::configure_G715_f16(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool rhs_lock_padding, const MatMulInfo &info)
+{
+ return configure_G715_f32(m, n, k, b, rhs_lock_padding, info);
+}
+
+MatMulKernelInfo ClMatMulNativeDefaultConfigValhall::configure_G715_u8(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool rhs_lock_padding, const MatMulInfo &info)
+{
+ ARM_COMPUTE_UNUSED(m, n, k, b, rhs_lock_padding);
+ return {info.adj_lhs(), info.adj_rhs(), /* m0 */ 4, /* n0 */ 16, /* k0 */ 4, /* export_to_cl_image */ false};
+}
+
+MatMulKernelInfo ClMatMulNativeDefaultConfigValhall::configure_G710_f32(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool rhs_lock_padding, const MatMulInfo &info)
+{
+ const MatMulNativeConfigsMatrix configs_mnkb_best_nt_nt = {
+ {3136, 64, 64, 36, 4, 4, 16, 1}, {4096, 48, 32, 36, 4, 4, 4, 1}, {688, 92, 68, 32, 2, 8, 4, 1},
+ {24, 464, 412, 24, 2, 8, 4, 1}, {112, 184, 144, 28, 4, 4, 16, 1}, {5776, 64, 32, 36, 2, 4, 16, 1},
+ {1568, 64, 40, 36, 2, 8, 8, 1}, {2920, 64, 64, 24, 4, 4, 16, 1}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_fallback_nt_nt = {
+ {3136, 64, 64, 36, 4, 4, 8, 0}, {4096, 48, 32, 36, 4, 4, 8, 0}, {688, 92, 68, 32, 5, 4, 4, 0},
+ {24, 464, 412, 24, 6, 2, 8, 0}, {112, 184, 144, 28, 6, 4, 4, 0}, {5776, 64, 32, 36, 5, 4, 4, 0},
+ {1568, 64, 40, 36, 4, 4, 8, 0}, {2920, 64, 64, 24, 4, 4, 8, 0}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_best_nt_t = {
+ {3136, 64, 64, 36, 4, 4, 4, 1}, {4096, 48, 32, 36, 2, 2, 16, 1}, {688, 92, 68, 32, 4, 4, 4, 1},
+ {24, 464, 412, 24, 6, 2, 8, 1}, {112, 184, 144, 28, 4, 2, 16, 1}, {5776, 64, 32, 36, 4, 4, 4, 1},
+ {1568, 64, 40, 36, 4, 4, 8, 1}, {2920, 64, 64, 24, 4, 4, 4, 1}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_fallback_nt_t = {
+ {3136, 64, 64, 36, 5, 4, 4, 0}, {4096, 48, 32, 36, 5, 4, 4, 0}, {688, 92, 68, 32, 5, 4, 4, 0},
+ {24, 464, 412, 24, 6, 2, 4, 0}, {112, 184, 144, 28, 5, 4, 4, 0}, {5776, 64, 32, 36, 5, 4, 4, 0},
+ {1568, 64, 40, 36, 5, 4, 4, 0}, {2920, 64, 64, 24, 6, 2, 4, 0}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_best_t_nt = {
+ {3136, 64, 64, 36, 4, 4, 16, 1}, {4096, 48, 32, 36, 4, 4, 4, 1}, {688, 92, 68, 32, 2, 8, 4, 1},
+ {24, 464, 412, 24, 2, 8, 4, 1}, {112, 184, 144, 28, 4, 4, 16, 1}, {5776, 64, 32, 36, 2, 8, 8, 1},
+ {1568, 64, 40, 36, 4, 4, 8, 1}, {2920, 64, 64, 24, 4, 4, 16, 1}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_fallback_t_nt = {
+ {3136, 64, 64, 36, 4, 4, 4, 0}, {4096, 48, 32, 36, 4, 4, 4, 0}, {688, 92, 68, 32, 4, 4, 4, 0},
+ {24, 464, 412, 24, 4, 4, 4, 0}, {112, 184, 144, 28, 4, 4, 4, 0}, {5776, 64, 32, 36, 4, 4, 8, 0},
+ {1568, 64, 40, 36, 4, 4, 4, 0}, {2920, 64, 64, 24, 4, 4, 4, 0}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_best_t_t = {
+ {3136, 64, 64, 36, 4, 4, 4, 1}, {4096, 48, 32, 36, 4, 4, 4, 1}, {688, 92, 68, 32, 4, 4, 4, 1},
+ {24, 464, 412, 24, 2, 2, 16, 1}, {112, 184, 144, 28, 4, 4, 4, 1}, {5776, 64, 32, 36, 4, 4, 4, 1},
+ {1568, 64, 40, 36, 4, 4, 4, 1}, {2920, 64, 64, 24, 4, 4, 4, 1}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_fallback_t_t = {
+ {3136, 64, 64, 36, 4, 4, 4, 0}, {4096, 48, 32, 36, 4, 4, 4, 0}, {688, 92, 68, 32, 4, 4, 4, 0},
+ {24, 464, 412, 24, 4, 2, 8, 0}, {112, 184, 144, 28, 4, 4, 4, 0}, {5776, 64, 32, 36, 4, 4, 4, 0},
+ {1568, 64, 40, 36, 4, 4, 4, 0}, {2920, 64, 64, 24, 4, 4, 4, 0}};
+
+ const bool adj_lhs = info.adj_lhs();
+ const bool adj_rhs = info.adj_rhs();
+
+ const MatMulNativeConfigsMatrix *configs_best_to_use = nullptr;
+ const MatMulNativeConfigsMatrix *configs_fallback_to_use = nullptr;
+
+ if ((adj_lhs == false) && (adj_rhs == false))
+ {
+ configs_best_to_use = &configs_mnkb_best_nt_nt;
+ configs_fallback_to_use = &configs_mnkb_fallback_nt_nt;
+ }
+ else if ((adj_lhs == false) && (adj_rhs == true))
+ {
+ configs_best_to_use = &configs_mnkb_best_nt_t;
+ configs_fallback_to_use = &configs_mnkb_fallback_nt_t;
+ }
+ else if ((adj_lhs == true) && (adj_rhs == false))
+ {
+ configs_best_to_use = &configs_mnkb_best_t_nt;
+ configs_fallback_to_use = &configs_mnkb_fallback_t_nt;
+ }
+ else
+ {
+ configs_best_to_use = &configs_mnkb_best_t_t;
+ configs_fallback_to_use = &configs_mnkb_fallback_t_t;
+ }
+
+ MatMulKernelInfo desc0 = find_info(*configs_best_to_use, adj_lhs, adj_rhs, m, n, k, b);
+ MatMulKernelInfo desc1 = find_info(*configs_fallback_to_use, adj_lhs, adj_rhs, m, n, k, b);
+
+ return select_info(desc0, desc1, m, n, k, b, DataType::F32, rhs_lock_padding);
+}
+
+MatMulKernelInfo ClMatMulNativeDefaultConfigValhall::configure_G710_f16(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool rhs_lock_padding, const MatMulInfo &info)
+{
+ const MatMulNativeConfigsMatrix configs_mnkb_best_nt_nt = {
+ {3136, 64, 64, 36, 4, 4, 16, 1}, {4096, 48, 32, 36, 4, 4, 8, 1}, {688, 92, 68, 32, 4, 4, 16, 1},
+ {24, 464, 412, 24, 4, 4, 4, 1}, {112, 184, 144, 28, 4, 4, 16, 1}, {5776, 64, 32, 36, 4, 4, 8, 1},
+ {1568, 64, 40, 36, 4, 4, 8, 1}, {2920, 64, 64, 24, 4, 4, 16, 1}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_fallback_nt_nt = {
+ {3136, 64, 64, 36, 6, 4, 8, 0}, {4096, 48, 32, 36, 6, 4, 8, 0}, {688, 92, 68, 32, 6, 4, 8, 0},
+ {24, 464, 412, 24, 4, 4, 8, 0}, {112, 184, 144, 28, 6, 4, 8, 0}, {5776, 64, 32, 36, 6, 4, 8, 0},
+ {1568, 64, 40, 36, 6, 4, 8, 0}, {2920, 64, 64, 24, 6, 4, 8, 0}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_best_nt_t = {
+ {3136, 64, 64, 36, 6, 4, 8, 1}, {4096, 48, 32, 36, 6, 4, 8, 1}, {688, 92, 68, 32, 4, 4, 4, 1},
+ {24, 464, 412, 24, 6, 2, 4, 1}, {112, 184, 144, 28, 4, 2, 16, 1}, {5776, 64, 32, 36, 6, 4, 8, 1},
+ {1568, 64, 40, 36, 6, 4, 8, 1}, {2920, 64, 64, 24, 6, 4, 8, 1}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_fallback_nt_t = {
+ {3136, 64, 64, 36, 6, 2, 16, 0}, {4096, 48, 32, 36, 5, 4, 8, 0}, {688, 92, 68, 32, 6, 2, 16, 0},
+ {24, 464, 412, 24, 6, 2, 16, 0}, {112, 184, 144, 28, 6, 2, 16, 0}, {5776, 64, 32, 36, 5, 4, 8, 0},
+ {1568, 64, 40, 36, 5, 4, 8, 0}, {2920, 64, 64, 24, 6, 2, 16, 0}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_best_t_nt = {
+ {3136, 64, 64, 36, 4, 4, 16, 1}, {4096, 48, 32, 36, 4, 4, 4, 1}, {688, 92, 68, 32, 4, 4, 4, 1},
+ {24, 464, 412, 24, 4, 4, 4, 1}, {112, 184, 144, 28, 4, 4, 4, 1}, {5776, 64, 32, 36, 4, 4, 4, 1},
+ {1568, 64, 40, 36, 4, 4, 4, 1}, {2920, 64, 64, 24, 4, 4, 4, 1}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_fallback_t_nt = {
+ {3136, 64, 64, 36, 4, 4, 4, 0}, {4096, 48, 32, 36, 4, 4, 4, 0}, {688, 92, 68, 32, 4, 4, 4, 0},
+ {24, 464, 412, 24, 4, 4, 4, 0}, {112, 184, 144, 28, 4, 4, 4, 0}, {5776, 64, 32, 36, 4, 4, 4, 0},
+ {1568, 64, 40, 36, 4, 4, 4, 0}, {2920, 64, 64, 24, 4, 4, 4, 0}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_best_t_t = {
+ {3136, 64, 64, 36, 4, 4, 16, 1}, {4096, 48, 32, 36, 4, 4, 8, 1}, {688, 92, 68, 32, 4, 4, 4, 1},
+ {24, 464, 412, 24, 4, 2, 8, 1}, {112, 184, 144, 28, 4, 2, 16, 1}, {5776, 64, 32, 36, 4, 4, 16, 1},
+ {1568, 64, 40, 36, 4, 4, 8, 1}, {2920, 64, 64, 24, 4, 4, 16, 1}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_fallback_t_t = {
+ {3136, 64, 64, 36, 4, 4, 8, 0}, {4096, 48, 32, 36, 4, 4, 8, 0}, {688, 92, 68, 32, 4, 4, 8, 0},
+ {24, 464, 412, 24, 4, 4, 8, 0}, {112, 184, 144, 28, 4, 4, 8, 0}, {5776, 64, 32, 36, 4, 4, 8, 0},
+ {1568, 64, 40, 36, 4, 4, 8, 0}, {2920, 64, 64, 24, 4, 4, 8, 0}};
+
+ const bool adj_lhs = info.adj_lhs();
+ const bool adj_rhs = info.adj_rhs();
+
+ const MatMulNativeConfigsMatrix *configs_best_to_use = nullptr;
+ const MatMulNativeConfigsMatrix *configs_fallback_to_use = nullptr;
+
+ if ((adj_lhs == false) && (adj_rhs == false))
+ {
+ configs_best_to_use = &configs_mnkb_best_nt_nt;
+ configs_fallback_to_use = &configs_mnkb_fallback_nt_nt;
+ }
+ else if ((adj_lhs == false) && (adj_rhs == true))
+ {
+ configs_best_to_use = &configs_mnkb_best_nt_t;
+ configs_fallback_to_use = &configs_mnkb_fallback_nt_t;
+ }
+ else if ((adj_lhs == true) && (adj_rhs == false))
+ {
+ configs_best_to_use = &configs_mnkb_best_t_nt;
+ configs_fallback_to_use = &configs_mnkb_fallback_t_nt;
+ }
+ else
+ {
+ configs_best_to_use = &configs_mnkb_best_t_t;
+ configs_fallback_to_use = &configs_mnkb_fallback_t_t;
+ }
+
+ MatMulKernelInfo desc0 = find_info(*configs_best_to_use, adj_lhs, adj_rhs, m, n, k, b);
+ MatMulKernelInfo desc1 = find_info(*configs_fallback_to_use, adj_lhs, adj_rhs, m, n, k, b);
+
+ return select_info(desc0, desc1, m, n, k, b, DataType::F16, rhs_lock_padding);
+}
+
+MatMulKernelInfo ClMatMulNativeDefaultConfigValhall::configure_G710_u8(
+ unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool rhs_lock_padding, const MatMulInfo &info)
+{
+ ARM_COMPUTE_UNUSED(rhs_lock_padding);
+
+ const MatMulNativeConfigsMatrix configs_mnkb_best_nt_nt = {
+ {3136, 64, 64, 36, 6, 4, 4, 0}, {4096, 48, 32, 36, 6, 4, 4, 0}, {688, 92, 68, 32, 2, 8, 4, 0},
+ {24, 464, 412, 24, 4, 4, 4, 0}, {112, 184, 144, 28, 6, 4, 4, 0}, {5776, 64, 32, 36, 6, 4, 4, 0},
+ {1568, 64, 40, 36, 6, 4, 4, 0}, {2920, 64, 64, 24, 5, 4, 4, 0}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_best_nt_t = {
+ {3136, 64, 64, 36, 4, 4, 16, 0}, {4096, 48, 32, 36, 4, 4, 16, 0}, {688, 92, 68, 32, 4, 4, 16, 0},
+ {24, 464, 412, 24, 6, 2, 16, 0}, {112, 184, 144, 28, 4, 4, 16, 0}, {5776, 64, 32, 36, 4, 4, 16, 0},
+ {1568, 64, 40, 36, 6, 4, 4, 0}, {2920, 64, 64, 24, 4, 4, 16, 0}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_best_t_nt = {
+ {3136, 64, 64, 36, 4, 4, 8, 0}, {4096, 48, 32, 36, 4, 4, 8, 0}, {688, 92, 68, 32, 4, 4, 4, 0},
+ {24, 464, 412, 24, 4, 4, 4, 0}, {112, 184, 144, 28, 4, 4, 8, 0}, {5776, 64, 32, 36, 4, 4, 8, 0},
+ {1568, 64, 40, 36, 4, 4, 8, 0}, {2920, 64, 64, 24, 4, 4, 8, 0}};
+
+ const MatMulNativeConfigsMatrix configs_mnkb_best_t_t = {
+ {3136, 64, 64, 36, 4, 2, 16, 0}, {4096, 48, 32, 36, 4, 4, 4, 0}, {688, 92, 68, 32, 4, 4, 8, 0},
+ {24, 464, 412, 24, 4, 2, 16, 0}, {112, 184, 144, 28, 4, 2, 16, 0}, {5776, 64, 32, 36, 4, 4, 4, 0},
+ {1568, 64, 40, 36, 4, 4, 8, 0}, {2920, 64, 64, 24, 4, 2, 16, 0}};
+
+ const bool adj_lhs = info.adj_lhs();
+ const bool adj_rhs = info.adj_rhs();
+
+ if ((adj_lhs == false) && (adj_rhs == false))
+ {
+ return find_info(configs_mnkb_best_nt_nt, adj_lhs, adj_rhs, m, n, k, b);
+ }
+ else if ((adj_lhs == false) && (adj_rhs == true))
+ {
+ return find_info(configs_mnkb_best_nt_t, adj_lhs, adj_rhs, m, n, k, b);
+ }
+ else if ((adj_lhs == true) && (adj_rhs == false))
+ {
+ return find_info(configs_mnkb_best_t_nt, adj_lhs, adj_rhs, m, n, k, b);
+ }
+ else
+ {
+ return find_info(configs_mnkb_best_t_t, adj_lhs, adj_rhs, m, n, k, b);
+ }
+}
+} // namespace cl_matmul
+} // namespace arm_compute
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-03 21:01:31 +0000