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https://github.com/vortexgpgpu/vortex.git
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65 lines
No EOL
1.7 KiB
C++
65 lines
No EOL
1.7 KiB
C++
// Copyright © 2019-2023
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifndef __VX_TENSOR_H__
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#define __VX_TENSOR_H__
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#include <stdint.h>
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#include <vx_intrinsics.h>
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#ifdef __cplusplus
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extern "C" {
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#endif
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#ifdef __cplusplus
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}
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#endif
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namespace tensor {
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enum frag_layout_t { row_major, col_major };
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enum mem_layout_t { mem_row_major, mem_col_major };
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template <typename T, frag_layout_t L>
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struct fragment {
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typedef T DType;
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static const frag_layout_t Layout = L;
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typedef T VType __attribute__((vector_size(8 * sizeof(void*))));
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VType data;
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};
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template <typename Frag>
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void fill_fragment(Frag &frag, size_t value) {
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// empty skeleton
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}
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template <typename Frag>
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void load_matrix_sync(Frag &frag, const void *ptr, size_t ld) {
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// empty skeleton
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}
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// Perform the matrix multiply-accumulate: D = A * B + C
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template <typename FragD, typename FragA, typename FragB, typename FragC>
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void mma_sync(FragD &D, const FragA &A, const FragB &B, const FragC &C) {
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// empty skeleton
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}
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// Store a fragment result back to global memory
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template <typename Type, typename Frag>
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void store_matrix_sync(void *ptr, const Frag &frag, size_t ld, mem_layout_t layout) {
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// empty skeleton
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}
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} // namespace wmma
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#endif // __VX_TENSOR_H__
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