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72 lines
2.7 KiB
Plaintext
Vendored
72 lines
2.7 KiB
Plaintext
Vendored
/**
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* llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
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*
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* MIT License
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*
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* Copyright (c) 2023-2024 The ggml authors
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#if !defined(GGML_USE_HIP) && !defined(GGML_USE_MUSA) && CUDART_VERSION >= 11700
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#define USE_CUB
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#endif // !defined(GGML_USE_HIP) && !defined(GGML_USE_MUSA) && CUDART_VERSION >= 11700
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#ifdef USE_CUB
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#include <cub/cub.cuh>
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using namespace cub;
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#endif // USE_CUB
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#include "sumrows.cuh"
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#include "sum.cuh"
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#include <cstdint>
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void sum_f32_cuda(ggml_cuda_pool & pool, const float * x, float * dst, const int64_t ne, cudaStream_t stream) {
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#ifdef USE_CUB
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size_t tmp_size = 0;
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DeviceReduce::Sum(nullptr, tmp_size, x, dst, ne, stream);
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ggml_cuda_pool_alloc<uint8_t> tmp_alloc(pool, tmp_size);
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DeviceReduce::Sum(tmp_alloc.ptr, tmp_size, x, dst, ne, stream);
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#else
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// Use (inefficient) sum_rows implementation as a fallback.
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// For AMD there is rocPRIM which could be used as a drop-in replacement via hipcub but this would require C++11 -> C++14.
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sum_rows_f32_cuda(x, dst, ne, 1, stream);
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GGML_UNUSED(pool);
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#endif // USE_CUB
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}
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void ggml_cuda_op_sum(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
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const ggml_tensor * src0 = dst->src[0];
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GGML_ASSERT(src0->type == GGML_TYPE_F32);
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GGML_ASSERT( dst->type == GGML_TYPE_F32);
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GGML_ASSERT(ggml_is_contiguous(src0));
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const float * src0_d = (const float *) src0->data;
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float * dst_d = (float *) dst->data;
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const int64_t ne = ggml_nelements(src0);
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ggml_cuda_pool & pool = ctx.pool();
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cudaStream_t stream = ctx.stream();
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sum_f32_cuda(pool, src0_d, dst_d, ne, stream);
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}
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