diff options
Diffstat (limited to 'examples/server')
| -rw-r--r-- | examples/server/README.md | 2 | ||||
| -rw-r--r-- | examples/server/server.cpp | 48 |
2 files changed, 50 insertions, 0 deletions
diff --git a/examples/server/README.md b/examples/server/README.md index bba513c..b011302 100644 --- a/examples/server/README.md +++ b/examples/server/README.md @@ -287,6 +287,8 @@ Test(); - `-m FNAME, --model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.bin`). - `-c N, --ctx-size N`: Set the size of the prompt context. The default is 512, but LLaMA models were built with a context of 2048, which will provide better results for longer input/inference. - `-ngl N, --n-gpu-layers N`: When compiled with appropriate support (currently CLBlast or cuBLAS), this option allows offloading some layers to the GPU for computation. Generally results in increased performance. +- `-mg i, --main-gpu i`: When using multiple GPUs this option controls which GPU is used for small tensors for which the overhead of splitting the computation across all GPUs is not worthwhile. The GPU in question will use slightly more VRAM to store a scratch buffer for temporary results. By default GPU 0 is used. Requires cuBLAS. +- `-ts SPLIT, --tensor-split SPLIT`: When using multiple GPUs this option controls how large tensors should be split across all GPUs. `SPLIT` is a comma-separated list of non-negative values that assigns the proportion of data that each GPU should get in order. For example, "3,2" will assign 60% of the data to GPU 0 and 40% to GPU 1. By default the data is split in proportion to VRAM but this may not be optimal for performance. Requires cuBLAS. - `--embedding`: Enable the embedding mode. **Completion function doesn't work in this mode**. - `--host`: Set the hostname or ip address to listen. Default `127.0.0.1`; - `--port`: Set the port to listen. Default: `8080`. diff --git a/examples/server/server.cpp b/examples/server/server.cpp index 9aa7db2..31d8087 100644 --- a/examples/server/server.cpp +++ b/examples/server/server.cpp @@ -401,6 +401,10 @@ void server_print_usage(int /*argc*/, char **argv, const gpt_params ¶ms) #ifdef LLAMA_SUPPORTS_GPU_OFFLOAD fprintf(stderr, " -ngl N, --n-gpu-layers N\n"); fprintf(stderr, " number of layers to store in VRAM\n"); + fprintf(stderr, " -ts SPLIT --tensor-split SPLIT\n"); + fprintf(stderr, " how to split tensors across multiple GPUs, comma-separated list of proportions, e.g. 3,1\n"); + fprintf(stderr, " how to split tensors across multiple GPUs, comma-separated list of proportions, e.g. 3,1\n"); + fprintf(stderr, " -mg i, --main-gpu i the GPU to use for scratch and small tensors\n" ); #endif fprintf(stderr, " -m FNAME, --model FNAME\n"); fprintf(stderr, " model path (default: %s)\n", params.model.c_str()); @@ -504,6 +508,50 @@ bool server_params_parse(int argc, char **argv, server_params &sparams, gpt_para fprintf(stderr, "warning: see main README.md for information on enabling GPU BLAS support\n"); #endif } + else if (arg == "--tensor-split" || arg == "-ts") + { + if (++i >= argc) + { + invalid_param = true; + break; + } +#ifdef GGML_USE_CUBLAS + std::string arg_next = argv[i]; + + // split string by , and / + const std::regex regex{R"([,/]+)"}; + std::sregex_token_iterator it{arg_next.begin(), arg_next.end(), regex, -1}; + std::vector<std::string> split_arg{it, {}}; + GGML_ASSERT(split_arg.size() <= LLAMA_MAX_DEVICES); + + for (size_t i = 0; i < LLAMA_MAX_DEVICES; ++i) + { + if (i < split_arg.size()) + { + params.tensor_split[i] = std::stof(split_arg[i]); + } + else + { + params.tensor_split[i] = 0.0f; + } + } +#else + fprintf(stderr, "WARNING: llama.cpp was compiled without cuBLAS. It is not possible to set a tensor split.\n"); +#endif // GGML_USE_CUBLAS + } + else if (arg == "--main-gpu" || arg == "-mg") + { + if (++i >= argc) + { + invalid_param = true; + break; + } +#ifdef GGML_USE_CUBLAS + params.main_gpu = std::stoi(argv[i]); +#else + fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to set a main GPU.\n"); +#endif + } else { fprintf(stderr, "error: unknown argument: %s\n", arg.c_str()); |