ggml : add RPC backend (#6829)

* 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

1 files changed, 74 insertions, 0 deletions

diff --git a/examples/rpc/README.md b/examples/rpc/README.md
new file mode 100644
index 00000000..325d0abc
--- /dev/null
+++ b/examples/rpc/README.md
@@ -0,0 +1,74 @@
+## 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 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.:
+```bash
+$ 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`:
+
+```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
+```