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-rw-r--r--examples/common.cpp16
-rw-r--r--examples/common.h1
-rw-r--r--examples/server/server.cpp15
3 files changed, 27 insertions, 5 deletions
diff --git a/examples/common.cpp b/examples/common.cpp
index fe7308b..e643984 100644
--- a/examples/common.cpp
+++ b/examples/common.cpp
@@ -352,7 +352,7 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
#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");
+ fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to set a main GPU.\n");
#endif
} else if (arg == "--tensor-split" || arg == "-ts") {
if (++i >= argc) {
@@ -376,13 +376,19 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
}
}
#else
- fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to set a tensor split.\n");
+ 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 == "--mul-mat-q" || arg == "-mmq") {
+#ifdef GGML_USE_CUBLAS
+ params.mul_mat_q = true;
+#else
+ fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to use mul_mat_q kernels.\n");
#endif // GGML_USE_CUBLAS
} else if (arg == "--low-vram" || arg == "-lv") {
#ifdef GGML_USE_CUBLAS
params.low_vram = true;
#else
- fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to set lower vram usage.\n");
+ fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to set lower vram usage.\n");
#endif // GGML_USE_CUBLAS
} else if (arg == "--no-mmap") {
params.use_mmap = false;
@@ -585,6 +591,9 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
fprintf(stdout, " how to split tensors across multiple GPUs, comma-separated list of proportions, e.g. 3,1\n");
fprintf(stdout, " -mg i, --main-gpu i the GPU to use for scratch and small tensors\n" );
fprintf(stdout, " -lv, --low-vram don't allocate VRAM scratch buffer\n" );
+ fprintf(stdout, " -mmq, --mul-mat-q use experimental mul_mat_q CUDA kernels instead of cuBLAS. TEMP!!!\n" );
+ fprintf(stdout, " Reduces VRAM usage by 700/970/1430 MiB for 7b/13b/33b but prompt processing speed\n" );
+ fprintf(stdout, " is still suboptimal, especially q2_K, q3_K, q5_K, and q6_K.\n" );
#endif
fprintf(stdout, " --mtest compute maximum memory usage\n");
fprintf(stdout, " --export export the computation graph to 'llama.ggml'\n");
@@ -637,6 +646,7 @@ struct llama_context_params llama_context_params_from_gpt_params(const gpt_param
lparams.main_gpu = params.main_gpu;
lparams.tensor_split = params.tensor_split;
lparams.low_vram = params.low_vram;
+ lparams.mul_mat_q = params.mul_mat_q;
lparams.seed = params.seed;
lparams.f16_kv = params.memory_f16;
lparams.use_mmap = params.use_mmap;
diff --git a/examples/common.h b/examples/common.h
index 1184f32..9744842 100644
--- a/examples/common.h
+++ b/examples/common.h
@@ -74,6 +74,7 @@ struct gpt_params {
size_t hellaswag_tasks = 400; // number of tasks to use when computing the HellaSwag score
bool low_vram = false; // if true, reduce VRAM usage at the cost of performance
+ bool mul_mat_q = false; // if true, use experimental mul_mat_q kernels
bool memory_f16 = true; // use f16 instead of f32 for memory kv
bool random_prompt = false; // do not randomize prompt if none provided
bool use_color = false; // use color to distinguish generations and inputs
diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index 83c0306..c072508 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -631,6 +631,9 @@ static void server_print_usage(const char *argv0, const gpt_params &params,
fprintf(stdout, " how to split tensors across multiple GPUs, comma-separated list of proportions, e.g. 3,1\n");
fprintf(stdout, " -mg i, --main-gpu i the GPU to use for scratch and small tensors\n");
fprintf(stdout, " -lv, --low-vram don't allocate VRAM scratch buffer\n");
+ fprintf(stdout, " -mmq, --mul-mat-q use experimental mul_mat_q CUDA kernels instead of cuBLAS. TEMP!!!\n" );
+ fprintf(stdout, " Reduces VRAM usage by 700/970/1430 MiB for 7b/13b/33b but prompt processing speed\n" );
+ fprintf(stdout, " is still suboptimal, especially q2_K, q3_K, q5_K, and q6_K.\n" );
#endif
fprintf(stdout, " -m FNAME, --model FNAME\n");
fprintf(stdout, " model path (default: %s)\n", params.model.c_str());
@@ -827,7 +830,7 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
}
}
#else
- LOG_WARNING("llama.cpp was compiled without cuBLAS. It is not possible to set a tensor split.", {});
+ LOG_WARNING("llama.cpp was compiled without cuBLAS. It is not possible to set a tensor split.\n", {});
#endif // GGML_USE_CUBLAS
}
else if (arg == "--low-vram" || arg == "-lv")
@@ -835,7 +838,15 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
#ifdef GGML_USE_CUBLAS
params.low_vram = true;
#else
- fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. It is not possible to set lower vram usage.\n");
+ LOG_WARNING("warning: llama.cpp was compiled without cuBLAS. It is not possible to set lower vram usage.\n", {});
+#endif // GGML_USE_CUBLAS
+ }
+ else if (arg == "--mul-mat-q" || arg == "-mmq")
+ {
+#ifdef GGML_USE_CUBLAS
+ params.mul_mat_q = true;
+#else
+ LOG_WARNING("warning: llama.cpp was compiled without cuBLAS. It is not possible to use mul_mat_q kernels.\n", {});
#endif // GGML_USE_CUBLAS
}
else if (arg == "--main-gpu" || arg == "-mg")