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Refactor OpenCL code to work more like the CUDA code, add missing functions

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0cc4m 2023-05-14 17:01:46 +02:00
parent 82bc517b9a
commit c77966524a
6 changed files with 658 additions and 188 deletions
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30
llama.cpp
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@ -11,6 +11,8 @@
#include "ggml.h"
#ifdef GGML_USE_CUBLAS
#include "ggml-cuda.h"
#elif defined(GGML_USE_CLBLAST)
#include "ggml-opencl.h"
#endif
#include <array>
@ -1027,7 +1029,7 @@ static void llama_model_load_internal(
ml->load_all_data(progress_callback, progress_callback_user_data, use_mlock ? &lctx.model.mlock_mmap : NULL);
model.mapping = std::move(ml->mapping);
#ifdef GGML_USE_CUBLAS
#if defined(GGML_USE_CUBLAS)
{
const int n_gpu = std::min(n_gpu_layers, int(hparams.n_layer));
@ -1053,6 +1055,32 @@ static void llama_model_load_internal(
fprintf(stderr, "%s: [cublas] total VRAM used: %zu MB\n", __func__, vram_total / 1024 / 1024);
}
#elif defined(GGML_USE_CLBLAST)
{
const int n_gpu = std::min(n_gpu_layers, int(hparams.n_layer));
fprintf(stderr, "%s: [opencl] offloading %d layers to GPU\n", __func__, n_gpu);
size_t vram_total = 0;
for (int i = 0; i < n_gpu; ++i) {
const auto & layer = model.layers[i];
ggml_cl_transform_tensor(layer.wq); vram_total += ggml_nbytes(layer.wq);
ggml_cl_transform_tensor(layer.wk); vram_total += ggml_nbytes(layer.wk);
ggml_cl_transform_tensor(layer.wv); vram_total += ggml_nbytes(layer.wv);
ggml_cl_transform_tensor(layer.wo); vram_total += ggml_nbytes(layer.wo);
ggml_cl_transform_tensor(layer.w1); vram_total += ggml_nbytes(layer.w1);
ggml_cl_transform_tensor(layer.w2); vram_total += ggml_nbytes(layer.w2);
ggml_cl_transform_tensor(layer.w3); vram_total += ggml_nbytes(layer.w3);
}
if (n_gpu_layers > (int) hparams.n_layer) {
fprintf(stderr, "%s: [cublas] offloading output layer to GPU\n", __func__);
ggml_cl_transform_tensor(model.output); vram_total += ggml_nbytes(model.output);
}
fprintf(stderr, "%s: [opencl] total VRAM used: %zu MB\n", __func__, vram_total / 1024 / 1024);
}
#else
(void) n_gpu_layers;
#endif