## Overview The `rpc-server` allows running `ggml` backend on a remote host. The RPC backend communicates with one or several instances of `rpc-server` and offloads computations to them. This can be used for distributed LLM inference with `llama.cpp` in the following way: ```mermaid flowchart TD rpcb---|TCP|srva rpcb---|TCP|srvb rpcb-.-|TCP|srvn subgraph hostn[Host N] srvn[rpc-server]-.-backend3["Backend (CUDA,Metal,etc.)"] end subgraph hostb[Host B] srvb[rpc-server]---backend2["Backend (CUDA,Metal,etc.)"] end subgraph hosta[Host A] srva[rpc-server]---backend["Backend (CUDA,Metal,etc.)"] end subgraph host[Main Host] ggml[llama.cpp]---rpcb[RPC backend] end style hostn stroke:#66,stroke-width:2px,stroke-dasharray: 5 5 ``` Each host can run a different backend, e.g. one with CUDA and another with Metal. You can also run multiple `rpc-server` instances on the same host, each with a different backend. ## Usage On each host, build the corresponding backend with `cmake` and add `-DLLAMA_RPC=ON` to the build options. For example, to build the CUDA backend with RPC support: ```bash mkdir build-rpc-cuda cd build-rpc-cuda cmake .. -DLLAMA_CUDA=ON -DLLAMA_RPC=ON cmake --build . --config Release ``` Then, start the `rpc-server` with the backend: ```bash $ bin/rpc-server -p 50052 create_backend: using CUDA backend ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: CUDA_USE_TENSOR_CORES: yes ggml_cuda_init: found 1 CUDA devices: Device 0: NVIDIA T1200 Laptop GPU, compute capability 7.5, VMM: yes Starting RPC server on 0.0.0.0:50052 ``` When using the CUDA backend, you can specify the device with the `CUDA_VISIBLE_DEVICES` environment variable, e.g.: ```bash $ CUDA_VISIBLE_DEVICES=0 bin/rpc-server -p 50052 ``` This way you can run multiple `rpc-server` instances on the same host, each with a different CUDA device. On the main host build `llama.cpp` only with `-DLLAMA_RPC=ON`: ```bash mkdir build-rpc cd build-rpc cmake .. -DLLAMA_RPC=ON cmake --build . --config Release ``` Finally, use the `--rpc` option to specify the host and port of each `rpc-server`: ```bash $ bin/main -m ../models/tinyllama-1b/ggml-model-f16.gguf -p "Hello, my name is" --repeat-penalty 1.0 -n 64 --rpc 192.168.88.10:50052,192.168.88.11:50052 -ngl 99 ```