Add skeleton of ClMatMulLowpNativeMMULKernel
The skeleton code consists of modifications
- to build the library with the quantized matmul kernel
- refactoring of some common utilities
- empty OpenCL Kernels for four configurations ([Lhs, Rhs] X [Nt, t])
- some validation tests and skeleton for functional tests
Resolves: COMPMID-6473
Change-Id: Id8401f789d34277dceb1f91afd68c9c88275618a
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10273
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/gpu/cl/kernels/helpers/MatMulKernelHelpers.cpp b/src/gpu/cl/kernels/helpers/MatMulKernelHelpers.cpp
new file mode 100644
index 0000000..2407c6c
--- /dev/null
+++ b/src/gpu/cl/kernels/helpers/MatMulKernelHelpers.cpp
@@ -0,0 +1,103 @@
+/*
+ * 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/gpu/cl/kernels/helpers/MatMulKernelHelpers.h"
+
+#include "arm_compute/core/Coordinates.h"
+#include "arm_compute/core/utils/helpers/AdjustVecSize.h"
+#include "arm_compute/core/utils/math/Math.h"
+
+#include "src/core/helpers/WindowHelpers.h"
+
+namespace arm_compute
+{
+namespace opencl
+{
+namespace kernels
+{
+Status validate_matmul_input_shapes(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const MatMulKernelInfo &matmul_kernel_info)
+{
+ const size_t lhs_k = matmul_kernel_info.adj_lhs ? lhs_shape.y() : lhs_shape.x();
+ const size_t rhs_k = matmul_kernel_info.adj_rhs ? rhs_shape.x() : rhs_shape.y();
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(lhs_k != rhs_k, "K dimension in Lhs and Rhs matrices must match.");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(lhs_shape.total_size() == 0, "Lhs tensor can't be empty");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(rhs_shape.total_size() == 0, "Rhs tensor can't be empty");
+
+ constexpr size_t batch_dim_start = 2;
+ for(size_t i = batch_dim_start; i < Coordinates::num_max_dimensions; ++i)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(lhs_shape[i] != rhs_shape[i], "Batch dimension broadcasting is not supported");
+ }
+
+ return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window_for_mmul_kernels(const ITensorInfo *lhs,
+ const ITensorInfo *rhs, const ITensorInfo *dst, const MatMulKernelInfo &matmul_kernel_info,
+ int mmul_m0, int mmul_n0)
+{
+ ARM_COMPUTE_UNUSED(lhs, rhs);
+
+ const Window win = calculate_max_window(*dst, Steps(1, 1));
+
+ // Collapse along the Z direction
+ // This collapse needs to be here in order to tune the Z dimension of LWS
+ Window collapsed = win.collapse(win, Window::DimZ);
+
+ // Reconfigure window size, one arm_matrix_multiply call needs 16 threads to finish.
+ Window::Dimension x_dimension = collapsed.x();
+ Window::Dimension y_dimension = collapsed.y();
+
+ const int m = dst->dimension(1);
+ const int n = dst->dimension(0);
+
+ const int m0 = std::min(matmul_kernel_info.m0, m);
+ const int n0 = adjust_vec_size(matmul_kernel_info.n0, n);
+
+ // Make M and N multiple of M0 and N0 respectively
+ const unsigned int ceil_to_multiple_n_n0 = ceil_to_multiple(n, n0);
+ const unsigned int ceil_to_multiple_m_m0 = ceil_to_multiple(m, m0);
+
+ // Divide M and N by M0 and N0 respectively
+ const unsigned int n_div_n0 = ceil_to_multiple_n_n0 / n0;
+ const unsigned int m_div_m0 = ceil_to_multiple_m_m0 / m0;
+
+ // Make n_div_n0 and m_div_m0 multiple of mmul_n0 and mmul_m0 respectively
+ const unsigned int ceil_to_multiple_n_div_n0_mmul_n0 = ceil_to_multiple(n_div_n0, mmul_n0);
+ const unsigned int ceil_to_multiple_m_div_m0_mmul_m0 = ceil_to_multiple(m_div_m0, mmul_m0);
+
+ // Ensure x_dimension is multiple of MMUL block size (mmul_m0 * mmul_n0)
+ x_dimension.set_end(ceil_to_multiple_n_div_n0_mmul_n0 * mmul_m0);
+ y_dimension.set_end(ceil_to_multiple_m_div_m0_mmul_m0 / mmul_m0);
+
+ collapsed.set(Window::DimX, x_dimension);
+ collapsed.set(Window::DimY, y_dimension);
+
+ return std::make_pair(Status{}, collapsed);
+}
+
+} // namespace kernels
+} // namespace opencl
+} // namespace arm_compute