vbatts/llama.cpp
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WIP full GPU acceleration

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This commit is contained in:
JohannesGaessler 2023-06-17 23:04:31 +02:00
parent 0c916d2357
commit 8f81cab1bc
1 changed files with 29 additions and 5 deletions
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34
libfalcon.cpp
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@ -1183,7 +1183,7 @@ static void falcon_model_load_internal(
} else // FALCON_7B
{
layer.input_layernorm = ml->get_tensor("transformer.h." + str_i +".input_layernorm.weight", {n_embd}, backend);
layer.input_layernorm_b = ml->get_tensor("transformer.h." + str_i +".input_layernorm.bias", {n_embd}, backend);
layer.input_layernorm_b = ml->get_tensor("transformer.h." + str_i +".input_layernorm.bias", {n_embd}, GGML_BACKEND_CPU);
}
layer.query_key_value = ml->get_tensor("transformer.h." + str_i +".self_attention.query_key_value.weight", {n_embd, (n_head_kv * 2 + n_head) * head_dim}, backend_split);
@ -1385,6 +1385,27 @@ static bool falcon_eval_internal(
const int i_gpu_start = n_layer - n_gpu_layers;
(void) i_gpu_start;
// offload functions set the tensor output backend to GPU
// tensors are GPU-accelerated if any input or the output has been offloaded
//
// with the low VRAM option VRAM scratch is disabled in llama_load_model_internal
// in that case ggml_cuda_assign_buffers has no effect
offload_func_t offload_func_nr = llama_nop; // nr = non-repeating
offload_func_t offload_func_kq = llama_nop;
offload_func_t offload_func_v = llama_nop;
#ifdef GGML_USE_CUBLAS
if (n_gpu_layers > n_layer) {
offload_func_nr = ggml_cuda_assign_buffers;
}
if (n_gpu_layers > n_layer + 1) {
offload_func_v = ggml_cuda_assign_buffers;
}
if (n_gpu_layers > n_layer + 2) {
offload_func_kq = ggml_cuda_assign_buffers;
}
#endif // GGML_USE_CUBLAS
for (int il = 0; il < n_layer; ++il) {
offload_func_t offload_func = llama_nop;
@ -1403,11 +1424,13 @@ static bool falcon_eval_internal(
{
layernorm_output = ggml_norm(ctx0, inpL);
ggml_tensor * il_a = ggml_mul(ctx0, layernorm_output, model.layers[il].input_layernorm);
offload_func(il_a);
layernorm_output = ggml_add(ctx0,
ggml_mul(ctx0,
ggml_repeat(ctx0, model.layers[il].input_layernorm, layernorm_output),
layernorm_output),
ggml_repeat(ctx0, model.layers[il].input_layernorm_b, layernorm_output));
il_a,
ggml_repeat(ctx0, model.layers[il].input_layernorm_b, layernorm_output));
offload_func(layernorm_output);
ggml_set_name(layernorm_output, "layernorm_output");
if (model.type == FALCON_40B || version == 40)
@ -1426,6 +1449,7 @@ static bool falcon_eval_internal(
// compute QKV
cur = ggml_mul_mat(ctx0, model.layers[il].query_key_value, cur);
// offload_func(cur);
// Note that the strides for Kcur, Vcur are set up so that the
// resulting views are misaligned with the tensor's storage