5e31828d3e
* ggml : add RPC backend The RPC backend proxies all operations to a remote server which runs a regular backend (CPU, CUDA, Metal, etc). * set TCP_NODELAY * add CI workflows * Address review comments * fix warning * implement llama_max_devices() for RPC * Address review comments * Address review comments * wrap sockfd into a struct * implement get_alignment and get_max_size * add get_device_memory * fix warning * win32 support * add README * readme : trim trailing whitespace * Address review comments * win32 fix * Address review comments * fix compile warnings on macos |
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| .. | ||
| CMakeLists.txt | ||
| README.md | ||
| rpc-server.cpp | ||
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:
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:
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:
$ bin/rpc-server 0.0.0.0 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.:
$ CUDA_VISIBLE_DEVICES=0 bin/rpc-server 0.0.0.0 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:
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:
$ 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