llama : ggml-backend integration (#4766)

* llama : ggml-backend integration

* ggml-backend : add names to buffers

* fix unmap after loading

* batched-bench : add tensor_split param

* llama : check for null tensor_split

* ggml-backend : increase GGML_MAX_BACKENDS

* improve graph splitting, partial fix for --no-kv-offload

* cuda : add ggml-backend split buffer support

* cuda : do not create buffer types for devices that don't exist (fixes usage without CUDA devices available)

* ggml : fix null backend dereference (#4807)

* ggml : fix null backend dereference

* ggml : also check ggml_backend_is_cpu

* test-backend-ops : check buffer allocation failures

* llama : add cparam (split_mode) and command line argument (--split-mode, -sm) to configure the split mode (none, layer or row)

* ggml : fix mul_mat_id work size

* llama : rewrite session kv load/set without graphs

* minor

* llama : only initialize used backends, free backends on context free

* llama : abort ctx if cuda backend init fails

* llama : rewrite lora with ggml-backend and compute on CPU

ggml-ci

* llama : only map to a backend buffer the region of the file mapping containing the tensors used in the buffer

* opencl : add ggml-backend buffer type

* cuda : only use batched_cublas with batched mat muls (fixes fp16 tg perf)

* llama : on Metal, by default offload the full model

ggml-ci

* metal : page align the data ptr (#4854)

* Apply suggestions from code review

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* cuda : fix split buffer free

* address review comments

* llama-bench : add split-mode parameter

* fix whitespace

* opencl : fix double initialization

* server : add --split-mode parameter

* use async copy and compute to improve multi-gpu performance

ggml-ci

* use async memcpys to copy the graph outputs to the CPU

* fix opencl

* use a host buffer for the cpu compute buffer for faster copies to the gpu

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

1 files changed, 35 insertions, 5 deletions

diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index 1d30a15a..c1ab8f9d 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -2005,12 +2005,15 @@ static void server_print_usage(const char *argv0, const gpt_params &params,
 #ifdef LLAMA_SUPPORTS_GPU_OFFLOAD
     printf("  -ngl N, --n-gpu-layers N\n");
     printf("                        number of layers to store in VRAM\n");
+    printf("  -sm SPLIT_MODE, --split-mode SPLIT_MODE\n");
+    printf("                        how to split the model across multiple GPUs, one of:\n");
+    printf("                          - none: use one GPU only\n");
+    printf("                          - layer (default): split layers and KV across GPUs\n");
+    printf("                          - row: split rows across GPUs\n");
     printf("  -ts SPLIT --tensor-split SPLIT\n");
-    printf("                        how to split tensors across multiple GPUs, comma-separated list of proportions, e.g. 3,1\n");
-    printf("  -mg i, --main-gpu i   the GPU to use for scratch and small tensors\n");
-    printf("  -nommq, --no-mul-mat-q\n");
-    printf("                        use cuBLAS instead of custom mul_mat_q CUDA kernels.\n");
-    printf("                        Not recommended since this is both slower and uses more VRAM.\n");
+    printf("                        fraction of the model to offload to each GPU, comma-separated list of proportions, e.g. 3,1\n");
+    printf("  -mg i, --main-gpu i   the GPU to use for the model (with split-mode = none),\n");
+    printf("                        or for intermediate results and KV (with split-mode = row)\n");
 #endif
     printf("  -m FNAME, --model FNAME\n");
     printf("                        model path (default: %s)\n", params.model.c_str());
@@ -2254,6 +2257,33 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
                         {{"n_gpu_layers", params.n_gpu_layers}});
 #endif
         }
+        else if (arg == "--split-mode" || arg == "-sm")
+        {
+            if (++i >= argc) {
+                invalid_param = true;
+                break;
+            }
+            std::string arg_next = argv[i];
+            if (arg_next == "none")
+            {
+                params.split_mode = LLAMA_SPLIT_NONE;
+            }
+            else if (arg_next == "layer")
+            {
+                params.split_mode = LLAMA_SPLIT_LAYER;
+            }
+            else if (arg_next == "row")
+            {
+                params.split_mode = LLAMA_SPLIT_ROW;
+            }
+            else {
+                invalid_param = true;
+                break;
+            }
+#ifndef GGML_USE_CUBLAS
+            fprintf(stderr, "warning: llama.cpp was compiled without cuBLAS. Setting the split mode has no effect.\n");
+#endif // GGML_USE_CUBLAS
+        }
         else if (arg == "--tensor-split" || arg == "-ts")
         {
             if (++i >= argc)