AI/turbopilot
1
0
Fork 0
mirror of https://github.com/ravenscroftj/turbopilot.git synced 2024-07-01 00:31:27 +00:00
Code Issues Packages Projects Releases Wiki Activity

add gpu offload for gpt-j models (codegen)

Browse Source
This commit is contained in:
James Ravenscroft 2023-08-26 16:11:16 +01:00
parent 604183380d
commit 0b408510f4
1 changed files with 50 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

50
src/gptj.cpp
View File

@ -6,6 +6,14 @@
#include <iostream>
#include <fstream>
#ifdef GGML_USE_CLBLAST
#include "ggml-opencl.h"
#endif
#ifdef GGML_USE_CUBLAS
#include "ggml-cuda.h"
#endif
#if defined(_MSC_VER)
#pragma warning(disable: 4244 4267) // possible loss of data
#endif
@ -455,6 +463,9 @@ bool GPTJModel::load_model(std::string fname) {
}
}
// key + value memory
{
const auto & hparams = model->hparams;
@ -553,6 +564,45 @@ bool GPTJModel::load_model(std::string fname) {
fin.close();
//#if defined(GGML_USE_CLBLAST) || defined(GGML_USE_CUBLAS)
if(config.n_gpu_layers > 0){
size_t vram_total = 0;
int gpu_layers = std::min(config.n_gpu_layers, model->hparams.n_layer);
spdlog::info("Attempting to offload {} layers to GPU", gpu_layers);
for(int i=0; i < gpu_layers; i++) {
const auto & layer = model->layers[i];
layer.c_attn_q_proj_w->backend = GGML_BACKEND_GPU;
layer.c_attn_k_proj_w->backend = GGML_BACKEND_GPU;
layer.c_attn_v_proj_w->backend = GGML_BACKEND_GPU;
layer.c_attn_proj_w->backend = GGML_BACKEND_GPU;
layer.c_mlp_fc_w->backend = GGML_BACKEND_GPU;
layer.c_mlp_proj_w->backend = GGML_BACKEND_GPU;
#if defined(GGML_USE_CLBLAST)
ggml_cl_transform_tensor(layer.c_attn_attn_w->data,layer.c_attn_attn_w); vram_total += ggml_nbytes(layer.c_attn_attn_w);
ggml_cl_transform_tensor(layer.c_attn_proj_w->data,layer.c_attn_proj_w); vram_total += ggml_nbytes(layer.c_attn_proj_w);
ggml_cl_transform_tensor(layer.c_mlp_fc_w->data,layer.c_mlp_fc_w); vram_total += ggml_nbytes(layer.c_mlp_fc_w);
ggml_cl_transform_tensor(layer.c_mlp_proj_w->data,layer.c_mlp_proj_w); vram_total += ggml_nbytes(layer.c_mlp_proj_w);
#else
ggml_cuda_transform_tensor(layer.c_attn_q_proj_w->data,layer.c_attn_q_proj_w); vram_total += ggml_nbytes(layer.c_attn_q_proj_w);
ggml_cuda_transform_tensor(layer.c_attn_k_proj_w->data,layer.c_attn_k_proj_w); vram_total += ggml_nbytes(layer.c_attn_k_proj_w);
ggml_cuda_transform_tensor(layer.c_attn_v_proj_w->data,layer.c_attn_v_proj_w); vram_total += ggml_nbytes(layer.c_attn_v_proj_w);
ggml_cuda_transform_tensor(layer.c_attn_proj_w->data,layer.c_attn_proj_w); vram_total += ggml_nbytes(layer.c_attn_proj_w);
ggml_cuda_transform_tensor(layer.c_mlp_fc_w->data,layer.c_mlp_fc_w); vram_total += ggml_nbytes(layer.c_mlp_fc_w);
ggml_cuda_transform_tensor(layer.c_mlp_proj_w->data,layer.c_mlp_proj_w); vram_total += ggml_nbytes(layer.c_mlp_proj_w);
#endif
}
spdlog::info("{}: [GPU] total VRAM used: {} MB\n", __func__, vram_total / 1024 / 1024);
}
//#endif // defined(GGML_USE_CLBLAST) || defined(GGML_USE_CUBLAS)
return true;
}