vbatts/llama.cpp
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Merge pull request #3 from hodlen/fix/gpu-dependency

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support powerinfer without GPU
This commit is contained in:
Jeremy Song 2023-12-12 15:40:29 +08:00 • committed by GitHub
commit e44f6401ec
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1 changed files with 15 additions and 2 deletions
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llama.cpp
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@ -2754,8 +2754,11 @@ struct llama_augmentation_model_loader {
// 1. gpu_idx;
// 2. gpu_bucket;
// 3. transformed ffn_down;
const int64_t ggml_aux_tensor_size = 4 * (100 * 100 + 5120*40*4 * ggml_tensor_overhead() + (int64_t)13824*5120*40*4);
printf("%ld\n", ggml_aux_tensor_size);
// const int64_t ggml_aux_tensor_size = 4 * (100 * 100 + 5120*40*4 * ggml_tensor_overhead() + (int64_t)13824*5120*40*4);
int model_layer = model->layers.size();
int ffn_dim = model->layers[0].ffn_up->ne[1];
const int64_t ggml_aux_tensor_size = 4 * (100 * 100 + model_layer*ffn_dim*sizeof(float) * ggml_tensor_overhead() );
printf("augmentation buffer: %ld\n", ggml_aux_tensor_size);
struct ggml_init_params params = {
/*.mem_size =*/ ggml_aux_tensor_size,
/*.mem_buffer =*/ nullptr,
@ -3966,12 +3969,14 @@ static struct ggml_tensor * llm_build_ffn_sparse(
third = cur;
struct ggml_tensor * tmp = ggml_mul_mat_idx(ctx, up, cur, idx, gpu_index);
cb(tmp, "ffn_up_sparse", il);
#ifdef GGML_USE_CUBLAS
struct ggml_tensor * tmp2 = ggml_mul_mat_special(ctx, up_gpu, cur, idx, gpu_bucket, up);
if (tmp2 != NULL) {
ggml_cuda_assign_buffers_no_alloc(tmp2);
cb(tmp2, "ffn_up_sparse_gpu", il);
}
tmp = ggml_add(ctx, tmp, tmp2);
#endif
if (up_b) {
@ -3985,12 +3990,14 @@ static struct ggml_tensor * llm_build_ffn_sparse(
third = cur;
cur = ggml_mul_mat_idx(ctx, gate, cur, idx, gpu_index);
cb(cur, "ffn_gate", il);
#ifdef GGML_USE_CUBLAS
tmp2 = ggml_mul_mat_special(ctx, gate_gpu, third, idx, gpu_bucket, gate);
if (tmp2 != NULL) {
ggml_cuda_assign_buffers_no_alloc(tmp2);
cb(tmp2, "ffn_up_sparse_gpu", il);
}
cur = ggml_add(ctx, cur, tmp2);
#endif
if (gate_b) {
cur = ggml_add(ctx, cur, gate_b);
@ -4017,14 +4024,20 @@ static struct ggml_tensor * llm_build_ffn_sparse(
}
third = cur;
#ifdef GGML_USE_CUBLAS
cur = ggml_axpy(ctx, down_gpu, cur, idx, gpu_bucket);
if (cur != NULL) {
ggml_cuda_assign_buffers_no_alloc(cur);
cb(cur, "ffn_down", il);
}
#endif
tmp = ggml_axpy(ctx, down_t, third, idx, gpu_index);
cb(tmp, "ffn_down_gpu", il);
#ifdef GGML_USE_CUBLAS
cur = ggml_add(ctx, cur, tmp);
#else
cur = tmp;
#endif
if (down_b) {
cur = ggml_add(ctx, cur, down_b);