aditya/llama.cpp
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Test-based VRAM scratch size + context adjustment (#2056)

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Johannes Gäßler 2023-07-01 21:47:26 +02:00 committed by GitHub
parent b213227067
commit befb3a3562
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1 changed files with 35 additions and 3 deletions
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llama.cpp
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@ -66,6 +66,7 @@ enum e_model {
MODEL_65B, MODEL_65B,
}; };
static const size_t kB = 1024;
static const size_t MB = 1024*1024; static const size_t MB = 1024*1024;
// computed for n_ctx == 2048 // computed for n_ctx == 2048
@ -129,6 +130,34 @@ static const std::map<e_model, size_t> & MEM_REQ_EVAL()
return k_sizes; return k_sizes;
} }
// amount of VRAM needed per batch size to hold temporary results
// the values for 3b and 65b are not derived from testing but instead chosen conservatively
static const std::map<e_model, size_t> & VRAM_REQ_SCRATCH_BASE()
{
static std::map<e_model, size_t> k_sizes = {
{ MODEL_3B, 512ull * kB },
{ MODEL_7B, 512ull * kB },
{ MODEL_13B, 640ull * kB },
{ MODEL_30B, 768ull * kB },
{ MODEL_65B, 1536ull * kB },
};
return k_sizes;
}
// amount of VRAM needed per batch size and context to hold temporary results
// the values for 3b and 65b are not derived from testing but instead chosen conservatively
static const std::map<e_model, size_t> & VRAM_REQ_SCRATCH_PER_CONTEXT()
{
static std::map<e_model, size_t> k_sizes = {
{ MODEL_3B, 128ull },
{ MODEL_7B, 128ull },
{ MODEL_13B, 160ull },
{ MODEL_30B, 208ull },
{ MODEL_65B, 416ull },
};
return k_sizes;
}
// default hparams (LLaMA 7B) // default hparams (LLaMA 7B)
struct llama_hparams { struct llama_hparams {
uint32_t n_vocab = 32000; uint32_t n_vocab = 32000;
@ -1118,11 +1147,14 @@ static void llama_model_load_internal(
fprintf(stderr, "%s: not allocating a VRAM scratch buffer due to low VRAM option\n", __func__); fprintf(stderr, "%s: not allocating a VRAM scratch buffer due to low VRAM option\n", __func__);
ggml_cuda_set_scratch_size(0); // disable scratch ggml_cuda_set_scratch_size(0); // disable scratch
} else { } else {
vram_scratch = n_batch * MB; const size_t vram_scratch_base = VRAM_REQ_SCRATCH_BASE().at(model.type);
const size_t vram_scratch_per_context = VRAM_REQ_SCRATCH_PER_CONTEXT().at(model.type);
vram_scratch = n_batch * (vram_scratch_base + n_ctx * vram_scratch_per_context);
ggml_cuda_set_scratch_size(vram_scratch); ggml_cuda_set_scratch_size(vram_scratch);
if (n_gpu_layers > 0) { if (n_gpu_layers > 0) {
fprintf(stderr, "%s: allocating batch_size x 1 MB = %zd MB VRAM for the scratch buffer\n", fprintf(stderr, "%s: allocating batch_size x (%zd kB + n_ctx x %zd B) = %zd MB VRAM for the scratch buffer\n",
__func__, vram_scratch / MB); __func__, vram_scratch_base / kB, vram_scratch_per_context,
(vram_scratch + MB - 1) / MB); // round up
} }
} }
#endif // GGML_USE_CUBLAS #endif // GGML_USE_CUBLAS