docs: Add documentation for s390x cpu implementation

docs/source/getting_started/installation.md

@@ -21,6 +21,7 @@ installation/ai_accelerator
   - Intel/AMD x86
   - ARM AArch64
   - Apple silicon
+  - IBM Z (S390X)
 - <project:installation/ai_accelerator.md>
   - Google TPU
   - Intel Gaudi

docs/source/getting_started/installation/cpu.md

@@ -36,6 +36,16 @@ vLLM is a Python library that supports the following CPU variants. Select your C
 
 ::::
 
+::::{tab-item} IBM Z (S390X)
+:sync: s390x
+
+:::{include} cpu/s390x.inc.md
+:start-after: "# Installation"
+:end-before: "## Requirements"
+:::
+
+::::
+
 :::::
 
 ## Requirements
@@ -75,6 +85,16 @@ vLLM is a Python library that supports the following CPU variants. Select your C
 
 ::::
 
+::::{tab-item} IBM Z (S390X)
+:sync: s390x
+
+:::{include} cpu/s390x.inc.md
+:start-after: "## Requirements"
+:end-before: "## Set up using Python"
+:::
+
+::::
+
 :::::
 
 ## Set up using Python
@@ -123,6 +143,16 @@ Currently, there are no pre-built CPU wheels.
 
 ::::
 
+::::{tab-item} IBM Z (s390x)
+:sync: s390x
+
+:::{include} cpu/s390x.inc.md
+:start-after: "### Build wheel from source"
+:end-before: "## Set up using Docker"
+:::
+
+::::
+
 :::::
 
 ## Set up using Docker
@@ -147,6 +177,10 @@ $ docker run -it \
 For ARM or Apple silicon, use `Dockerfile.arm`
 ::::
 
+::::{tip}
+For IBM Z (s390x), use `Dockerfile.s390x` and in `docker run` use flag `--dtype float`
+::::
+
 ## Supported features
 
 vLLM CPU backend supports the following vLLM features:

docs/source/getting_started/installation/cpu/s390x.inc.md

@@ -0,0 +1,62 @@
+# Installation
+
+vLLM has experimental support for s390x architecture on IBM Z platform. For now, users shall build from the vLLM source to natively run on IBM Z platform.
+
+Currently the CPU implementation for s390x architecture supports FP32 datatype only.
+
+:::{attention}
+There are no pre-built wheels or images for this device, so you must build vLLM from source.
+:::
+
+## Requirements
+
+- OS: `Linux`
+- SDK: `gcc/g++ >= 12.3.0` or later with Command Line Tools
+- Instruction Set Architecture (ISA): VXE support is required. Works with Z14 and above.
+- Build install python packages: `pyarrow`, `torch` and `torchvision`
+
+## Set up using Python
+
+### Pre-built wheels
+
+### Build wheel from source
+
+Install the following packages from the package manager before building the vLLM. For example on RHEL 9.4:
+
+```console
+dnf install -y \
+    which procps findutils tar vim git gcc g++ make patch make cython zlib-devel \
+    libjpeg-turbo-devel libtiff-devel libpng-devel libwebp-devel freetype-devel harfbuzz-devel \
+    openssl-devel openblas openblas-devel wget autoconf automake libtool cmake numactl-devel
+```
+
+Install rust>=1.80 which is needed for `outlines-core` and `uvloop` python packages installation.
+
+```console
+curl https://sh.rustup.rs -sSf | sh -s -- -y && \
+    . "$HOME/.cargo/env"
+```
+
+Execute the following commands to build and install vLLM from the source.
+
+::::{tip}
+Please build the following dependencies, `torchvision`, `pyarrow` from the source before building vLLM.
+::::
+
+```console
+    sed -i '/^torch/d' requirements-build.txt    # remove torch from requirements-build.txt since we use nightly builds
+    pip install -v \
+        --extra-index-url https://download.pytorch.org/whl/nightly/cpu \
+        -r requirements-build.txt \
+        -r requirements-cpu.txt \
+    VLLM_TARGET_DEVICE=cpu python setup.py bdist_wheel && \
+    pip install dist/*.whl
+```
+
+## Set up using Docker
+
+### Pre-built images
+
+### Build image from source
+
+## Extra information