1 files changed, 108 insertions, 0 deletions
diff --git a/src/gpu/cl/kernels/helpers/MatMulKernelHelpers.cpp b/src/gpu/cl/kernels/helpers/MatMulKernelHelpers.cpp
new file mode 100644
index 0000000000..689a743fdf
--- /dev/null
+++ b/src/gpu/cl/kernels/helpers/MatMulKernelHelpers.cpp
@@ -0,0 +1,108 @@
+/*
+ * 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