114 lines
4.0 KiB
Plaintext
114 lines
4.0 KiB
Plaintext
/**
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* llama.cpp - commit ee459f40f65810a810151b24eba5b8bd174ceffe - 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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#include "mmq.cuh"
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void ggml_cuda_op_mul_mat_q(
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ggml_backend_cuda_context & ctx,
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const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, const char * src0_dd_i, const float * src1_ddf_i,
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const char * src1_ddq_i, float * dst_dd_i, const int64_t row_low, const int64_t row_high, const int64_t src1_ncols,
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const int64_t src1_padded_row_size, cudaStream_t stream) {
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const int64_t ne00 = src0->ne[0];
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const int64_t nb01 = src0->nb[1];
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const int64_t ne10 = src1->ne[0];
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GGML_ASSERT(ne10 % QK8_1 == 0);
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const int64_t ne0 = dst->ne[0];
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const int64_t row_diff = row_high - row_low;
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const int64_t stride00 = nb01 / ggml_type_size(src0->type);
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int id = ggml_cuda_get_device();
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const int compute_capability = ggml_cuda_info().devices[id].cc;
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// the main device has a larger memory buffer to hold the results from all GPUs
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// nrows_dst == nrows of the matrix that the kernel writes into
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const int64_t nrows_dst = id == ctx.device ? ne0 : row_diff;
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const mmq_args args = {src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, stride00, src1_padded_row_size, src1_ncols, nrows_dst};
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switch (src0->type) {
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case GGML_TYPE_Q4_0:
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mul_mat_q_case<GGML_TYPE_Q4_0>(args, stream);
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break;
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case GGML_TYPE_Q4_1:
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mul_mat_q_case<GGML_TYPE_Q4_1>(args, stream);
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break;
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case GGML_TYPE_Q5_0:
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mul_mat_q_case<GGML_TYPE_Q5_0>(args, stream);
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break;
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case GGML_TYPE_Q5_1:
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mul_mat_q_case<GGML_TYPE_Q5_1>(args, stream);
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break;
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case GGML_TYPE_Q8_0:
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mul_mat_q_case<GGML_TYPE_Q8_0>(args, stream);
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break;
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case GGML_TYPE_Q2_K:
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mul_mat_q_case<GGML_TYPE_Q2_K>(args, stream);
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break;
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case GGML_TYPE_Q3_K:
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mul_mat_q_case<GGML_TYPE_Q3_K>(args, stream);
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break;
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case GGML_TYPE_Q4_K:
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mul_mat_q_case<GGML_TYPE_Q4_K>(args, stream);
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break;
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case GGML_TYPE_Q5_K:
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mul_mat_q_case<GGML_TYPE_Q5_K>(args, stream);
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break;
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case GGML_TYPE_Q6_K:
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mul_mat_q_case<GGML_TYPE_Q6_K>(args, stream);
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break;
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default:
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GGML_ASSERT(false);
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break;
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}
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GGML_UNUSED(src1);
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GGML_UNUSED(dst);
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GGML_UNUSED(src1_ddf_i);
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}
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bool ggml_cuda_supports_mmq(enum ggml_type type) {
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switch (type) {
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case GGML_TYPE_Q4_0:
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case GGML_TYPE_Q4_1:
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case GGML_TYPE_Q5_0:
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case GGML_TYPE_Q5_1:
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case GGML_TYPE_Q8_0:
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case GGML_TYPE_Q2_K:
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case GGML_TYPE_Q3_K:
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case GGML_TYPE_Q4_K:
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case GGML_TYPE_Q5_K:
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case GGML_TYPE_Q6_K:
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return true;
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default:
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return false;
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}
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}
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