mirror of
https://github.com/ggml-org/llama.cpp.git
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91 lines
3.1 KiB
C++
91 lines
3.1 KiB
C++
//
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// MIT license
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// Copyright (C) 2024 Intel Corporation
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// SPDX-License-Identifier: MIT
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//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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#ifndef GGML_SYCL_GEMM_HPP
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#define GGML_SYCL_GEMM_HPP
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#include "ggml-sycl.h"
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#if GGML_SYCL_DNNL
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#include "dnnl.hpp"
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#include "dnnl_sycl.hpp"
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class DnnlGemmWrapper {
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public:
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using dt = dnnl::memory::data_type;
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using tag = dnnl::memory::format_tag;
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template<typename T>
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static constexpr dt to_dt() {
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if constexpr (std::is_same_v<T, float>) return dt::f32;
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else if constexpr (std::is_same_v<T, sycl::half>) return dt::f16;
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else static_assert(0);
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}
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static void gemm(ggml_backend_sycl_context & ctx, int m, int n, int k,
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const void * a, dt at, dnnl_dim_t stra0, dnnl_dim_t stra1, dnnl_dim_t stra2,
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const void * b, dt bt, dnnl_dim_t strb0, dnnl_dim_t strb1, dnnl_dim_t strb2,
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void * c, dt ct, const queue_ptr & q, dnnl_dim_t batches_a, dnnl_dim_t batches_b) {
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auto stream = ctx.stream_dnnl(q);
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auto eng = ctx.engine_dnnl(q);
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dnnl::memory::dims a_dims = {batches_a, m, k };
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dnnl::memory::dims a_strides = {stra2, stra1, stra0};
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const auto a_in_md = dnnl::memory::desc(a_dims, at, a_strides);
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dnnl::memory::dims b_dims = {batches_b, k, n };
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dnnl::memory::dims b_strides = {strb2, strb0, strb1};
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const auto b_in_md = dnnl::memory::desc(b_dims, bt, b_strides);
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dnnl::memory::dims c_dims = { std::max(batches_a, batches_b), m, n};
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dnnl::memory::dims c_strides = {m*n, 1, m };
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const auto c_md = dnnl::memory::desc(c_dims, ct, c_strides);
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dnnl::primitive_attr primitive_attr;
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primitive_attr.set_scratchpad_mode(dnnl::scratchpad_mode::user);
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#ifdef GGML_SYCL_F16
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primitive_attr.set_fpmath_mode(dnnl::fpmath_mode::f16);
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#endif
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auto a_mem = dnnl::memory(a_in_md, eng, const_cast<void*>(a));
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auto b_mem = dnnl::memory(b_in_md, eng, const_cast<void*>(b));
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auto matmul_pd = dnnl::matmul::primitive_desc(eng, a_in_md, b_in_md, c_md, primitive_attr);
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auto c_mem = dnnl::memory(matmul_pd.dst_desc(), eng, c);
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auto scratchpad_md = matmul_pd.scratchpad_desc();
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auto scratchpad_mem = ctx.get_scratchpad_mem(scratchpad_md, eng, q);
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auto matmul_prim = dnnl::matmul(matmul_pd);
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std::unordered_map<int, dnnl::memory> matmul_args;
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matmul_args.insert({ DNNL_ARG_SRC, a_mem });
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matmul_args.insert({ DNNL_ARG_WEIGHTS, b_mem });
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matmul_args.insert({ DNNL_ARG_DST, c_mem });
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matmul_args.insert({ DNNL_ARG_SCRATCHPAD, scratchpad_mem });
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matmul_prim.execute(stream, matmul_args);
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}
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static void row_gemm(ggml_backend_sycl_context & ctx, int m, int n, int k,
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const void * a, dt at, const void * b, dt bt, void * c, dt ct, const queue_ptr & q) {
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gemm(ctx, m, n, k, a, at, 1, k, k * m, b, bt, 1, k, n * k, c, ct, q, 1, 1);
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}
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};
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#endif
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#endif // GGML_SYCL_GEMM_HPP
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