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	update llama-rpc-server bin name + doc
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		@@ -1,2 +1,3 @@
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add_executable(rpc-server rpc-server.cpp)
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target_link_libraries(rpc-server PRIVATE ggml llama)
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set(TARGET llama-rpc-server)
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add_executable(${TARGET} rpc-server.cpp)
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target_link_libraries(${TARGET} PRIVATE ggml llama)
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@@ -1,7 +1,7 @@
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## Overview
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The `rpc-server` allows  running `ggml` backend on a remote host.
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The RPC backend communicates with one or several instances of `rpc-server` and offloads computations to them.
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`llama-rpc-server` allows  running `ggml` backend on a remote host.
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The RPC backend communicates with one or several instances of `llama-rpc-server` and offloads computations to them.
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This can be used for distributed LLM inference with `llama.cpp` in the following way:
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```mermaid
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@@ -10,13 +10,13 @@ flowchart TD
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    rpcb---|TCP|srvb
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    rpcb-.-|TCP|srvn
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    subgraph hostn[Host N]
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    srvn[rpc-server]-.-backend3["Backend (CUDA,Metal,etc.)"]
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    srvn[llama-rpc-server]-.-backend3["Backend (CUDA,Metal,etc.)"]
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    end
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    subgraph hostb[Host B]
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    srvb[rpc-server]---backend2["Backend (CUDA,Metal,etc.)"]
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    srvb[llama-rpc-server]---backend2["Backend (CUDA,Metal,etc.)"]
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    end
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    subgraph hosta[Host A]
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    srva[rpc-server]---backend["Backend (CUDA,Metal,etc.)"]
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    srva[llama-rpc-server]---backend["Backend (CUDA,Metal,etc.)"]
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    end
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    subgraph host[Main Host]
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    ggml[llama.cpp]---rpcb[RPC backend]
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@@ -25,7 +25,7 @@ flowchart TD
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```
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Each host can run a different backend, e.g. one with CUDA and another with Metal.
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You can also run multiple `rpc-server` instances on the same host, each with a different backend.
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You can also run multiple `llama-rpc-server` instances on the same host, each with a different backend.
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## Usage
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@@ -33,16 +33,14 @@ On each host, build the corresponding backend with `cmake` and add `-DLLAMA_RPC=
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For example, to build the CUDA backend with RPC support:
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```bash
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mkdir build-rpc-cuda
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cd build-rpc-cuda
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cmake .. -DLLAMA_CUDA=ON -DLLAMA_RPC=ON
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cmake --build . --config Release
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cmake -B build-rpc-cuda -DLLAMA_CUDA=ON -DLLAMA_RPC=ON
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cmake --build build-rpc-cuda --config Release
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```
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Then, start the `rpc-server` with the backend:
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Then, start `llama-rpc-server` with the backend:
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```bash
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$ bin/rpc-server -p 50052
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$ bin/llama-rpc-server -p 50052
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create_backend: using CUDA backend
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ggml_cuda_init: GGML_CUDA_FORCE_MMQ:   no
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ggml_cuda_init: CUDA_USE_TENSOR_CORES: yes
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@@ -53,21 +51,19 @@ Starting RPC server on 0.0.0.0:50052
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When using the CUDA backend, you can specify the device with the `CUDA_VISIBLE_DEVICES` environment variable, e.g.:
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```bash
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$ CUDA_VISIBLE_DEVICES=0 bin/rpc-server -p 50052
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$ CUDA_VISIBLE_DEVICES=0 bin/llama-rpc-server -p 50052
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```
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This way you can run multiple `rpc-server` instances on the same host, each with a different CUDA device.
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This way you can run multiple `llama-rpc-server` instances on the same host, each with a different CUDA device.
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On the main host build `llama.cpp` only with `-DLLAMA_RPC=ON`:
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```bash
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mkdir build-rpc
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cd build-rpc
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cmake .. -DLLAMA_RPC=ON
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cmake --build . --config Release
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cmake -B build-rpc -DLLAMA_RPC=ON
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cmake --build build-rpc --config Release -t -j
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```
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Finally, use the `--rpc` option to specify the host and port of each `rpc-server`:
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Finally, use the `--rpc` option to specify the host and port of each `llama-rpc-server`:
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```bash
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$ bin/llama-cli -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
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