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[Hardware][IBM Z]Enable v1 for s390x and s390x dockerfile fixes (#22725)

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Signed-off-by: Nikhil Suryawanshi <suryawanshin74@gmail.com>
This commit is contained in:
Nikhil Suryawanshi 2025-08-19 10:10:37 +05:30 committed by GitHub
parent e9d6a3db69
commit 78dba404ad
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GPG Key ID: B5690EEEBB952194
7 changed files with 96 additions and 18 deletions
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87
docker/Dockerfile.s390x
View File

@ -16,7 +16,7 @@ ENV LANG=C.UTF-8 \
RUN microdnf install -y \
which procps findutils tar vim git gcc gcc-gfortran g++ make patch zlib-devel \
libjpeg-turbo-devel libtiff-devel libpng-devel libwebp-devel freetype-devel harfbuzz-devel \
openssl-devel openblas openblas-devel autoconf automake libtool cmake numpy && \
openssl-devel openblas openblas-devel autoconf automake libtool cmake numpy libsndfile && \
microdnf clean all
# Python Installation
@ -136,6 +136,71 @@ RUN --mount=type=cache,target=/root/.cache/uv \
mkdir -p /tmp/hf-xet/dist && \
cp dist/*.whl /tmp/hf-xet/dist/
# Build numba
FROM python-install AS numba-builder
ARG MAX_JOBS
ARG NUMBA_VERSION=0.61.2
WORKDIR /tmp
# Clone all required dependencies
RUN --mount=type=cache,target=/root/.cache/uv \
microdnf install ninja-build gcc gcc-c++ -y && \
git clone --recursive https://github.com/llvm/llvm-project.git -b llvmorg-15.0.7 && \
git clone --recursive https://github.com/numba/llvmlite.git -b v0.44.0 && \
git clone --recursive https://github.com/numba/numba.git -b ${NUMBA_VERSION} && \
cd llvm-project && mkdir build && cd build && \
uv pip install 'cmake<4' setuptools numpy && \
export PREFIX=/usr/local && CMAKE_ARGS="${CMAKE_ARGS} -DLLVM_ENABLE_PROJECTS=lld;libunwind;compiler-rt" \
CFLAGS="$(echo $CFLAGS | sed 's/-fno-plt //g')" \
CXXFLAGS="$(echo $CXXFLAGS | sed 's/-fno-plt //g')" \
CMAKE_ARGS="${CMAKE_ARGS} -DFFI_INCLUDE_DIR=$PREFIX/include" \
CMAKE_ARGS="${CMAKE_ARGS} -DFFI_LIBRARY_DIR=$PREFIX/lib" \
cmake -DCMAKE_INSTALL_PREFIX="${PREFIX}" \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_LIBRARY_PATH="${PREFIX}" \
-DLLVM_ENABLE_LIBEDIT=OFF \
-DLLVM_ENABLE_LIBXML2=OFF \
-DLLVM_ENABLE_RTTI=ON \
-DLLVM_ENABLE_TERMINFO=OFF \
-DLLVM_INCLUDE_BENCHMARKS=OFF \
-DLLVM_INCLUDE_DOCS=OFF \
-DLLVM_INCLUDE_EXAMPLES=OFF \
-DLLVM_INCLUDE_GO_TESTS=OFF \
-DLLVM_INCLUDE_TESTS=OFF \
-DLLVM_INCLUDE_UTILS=ON \
-DLLVM_INSTALL_UTILS=ON \
-DLLVM_UTILS_INSTALL_DIR=libexec/llvm \
-DLLVM_BUILD_LLVM_DYLIB=OFF \
-DLLVM_LINK_LLVM_DYLIB=OFF \
-DLLVM_EXPERIMENTAL_TARGETS_TO_BUILD=WebAssembly \
-DLLVM_ENABLE_FFI=ON \
-DLLVM_ENABLE_Z3_SOLVER=OFF \
-DLLVM_OPTIMIZED_TABLEGEN=ON \
-DCMAKE_POLICY_DEFAULT_CMP0111=NEW \
-DCOMPILER_RT_BUILD_BUILTINS=ON \
-DCOMPILER_RT_BUILTINS_HIDE_SYMBOLS=OFF \
-DCOMPILER_RT_BUILD_LIBFUZZER=OFF \
-DCOMPILER_RT_BUILD_CRT=OFF \
-DCOMPILER_RT_BUILD_MEMPROF=OFF \
-DCOMPILER_RT_BUILD_PROFILE=OFF \
-DCOMPILER_RT_BUILD_SANITIZERS=OFF \
-DCOMPILER_RT_BUILD_XRAY=OFF \
-DCOMPILER_RT_BUILD_GWP_ASAN=OFF \
-DCOMPILER_RT_BUILD_ORC=OFF \
-DCOMPILER_RT_INCLUDE_TESTS=OFF \
${CMAKE_ARGS} -GNinja ../llvm \
&& ninja install . && \
# build llvmlite
cd ../../llvmlite && python setup.py bdist_wheel && \
cd ../numba && \
if ! grep '#include "dynamic_annotations.h"' numba/_dispatcher.cpp; then \
sed -i '/#include "internal\/pycore_atomic.h"/i\#include "dynamic_annotations.h"' numba/_dispatcher.cpp; \
fi && python setup.py bdist_wheel
# Final build stage
FROM python-install AS vllm-cpu
ARG PYTHON_VERSION
@ -163,23 +228,30 @@ RUN --mount=type=cache,target=/root/.cache/uv \
--mount=type=bind,from=torch-vision,source=/tmp/vision/dist,target=/tmp/vision-wheels/ \
--mount=type=bind,from=hf-xet-builder,source=/tmp/hf-xet/dist,target=/tmp/hf-xet-wheels/ \
--mount=type=bind,from=torch,source=/tmp/pytorch/dist,target=/tmp/torch-wheels/ \
--mount=type=bind,from=numba-builder,source=/tmp/llvmlite/dist,target=/tmp/llvmlite-wheels/ \
--mount=type=bind,from=numba-builder,source=/tmp/numba/dist,target=/tmp/numba-wheels/ \
sed -i '/^torch/d' requirements/build.txt && \
ARROW_WHL_FILE=$(ls /tmp/arrow-wheels/pyarrow-*.whl | head -n 1) && \
VISION_WHL_FILE=$(ls /tmp/vision-wheels/*.whl | head -n 1) && \
HF_XET_WHL_FILE=$(ls /tmp/hf-xet-wheels/*.whl | head -n 1) && \
TORCH_WHL_FILE=$(ls /tmp/torch-wheels/*.whl | head -n 1) && \
ARROW_WHL_FILE=$(ls /tmp/arrow-wheels/pyarrow-*.whl) && \
VISION_WHL_FILE=$(ls /tmp/vision-wheels/*.whl) && \
HF_XET_WHL_FILE=$(ls /tmp/hf-xet-wheels/*.whl) && \
TORCH_WHL_FILE=$(ls /tmp/torch-wheels/*.whl) && \
LLVM_WHL_FILE=$(ls /tmp/llvmlite-wheels/*.whl) && \
NUMBA_WHL_FILE=$(ls /tmp/numba-wheels/*.whl) && \
uv pip install -v \
$ARROW_WHL_FILE \
$VISION_WHL_FILE \
$HF_XET_WHL_FILE \
$TORCH_WHL_FILE \
$LLVM_WHL_FILE \
$NUMBA_WHL_FILE \
--index-strategy unsafe-best-match \
-r requirements/build.txt \
-r requirements/cpu.txt
-r requirements/cpu.txt
# Build and install vllm
RUN --mount=type=cache,target=/root/.cache/uv \
VLLM_TARGET_DEVICE=cpu python setup.py bdist_wheel && \
VLLM_TARGET_DEVICE=cpu VLLM_CPU_MOE_PREPACK=0 python setup.py bdist_wheel && \
uv pip install "$(echo dist/*.whl)[tensorizer]"
# setup non-root user for vllm
@ -196,4 +268,3 @@ WORKDIR /home/vllm
# Set the default entrypoint
ENTRYPOINT ["python", "-m", "vllm.entrypoints.openai.api_server"]

3
requirements/common.txt
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@ -20,7 +20,8 @@ prometheus-fastapi-instrumentator >= 7.0.0
tiktoken >= 0.6.0 # Required for DBRX tokenizer
lm-format-enforcer >= 0.10.11, < 0.11
llguidance >= 0.7.11, < 0.8.0; platform_machine == "x86_64" or platform_machine == "arm64" or platform_machine == "aarch64"
outlines_core == 0.2.10
outlines_core == 0.2.10 ; platform_machine != "s390x"
outlines == 0.1.11 ; platform_machine == "s390x"
# required for outlines backend disk cache
diskcache == 5.6.3
lark == 1.2.2

4
requirements/cpu.txt
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@ -1,8 +1,8 @@
# Common dependencies
-r common.txt
numba == 0.60.0; python_version == '3.9' # v0.61 doesn't support Python 3.9. Required for N-gram speculative decoding
numba == 0.61.2; python_version > '3.9'
numba == 0.60.0; python_version == '3.9' and platform_machine != "s390x" # v0.61 doesn't support Python 3.9. Required for N-gram speculative decoding
numba == 0.61.2; python_version > '3.9' and platform_machine != "s390x"
# Dependencies for CPUs
packaging>=24.2

7
vllm/engine/arg_utils.py
View File

@ -1076,12 +1076,13 @@ class EngineArgs:
# Set default arguments for V0 or V1 Engine.
if use_v1:
self._set_default_args_v1(usage_context, model_config)
# Disable chunked prefill for POWER (ppc64le)/ARM CPUs in V1
# Disable chunked prefill for POWER (ppc64le)/ARM/s390x CPUs in V1
if current_platform.is_cpu(
) and current_platform.get_cpu_architecture() in (
CpuArchEnum.POWERPC, CpuArchEnum.ARM):
CpuArchEnum.POWERPC, CpuArchEnum.S390X, CpuArchEnum.ARM):
logger.info(
"Chunked prefill is not supported for ARM and POWER CPUs; "
"Chunked prefill is not supported for ARM and POWER "
"and S390X CPUs; "
"disabling it for V1 backend.")
self.enable_chunked_prefill = False
else:

5
vllm/platforms/cpu.py
View File

@ -332,5 +332,6 @@ class CpuPlatform(Platform):
supplied model configuration.
"""
arch = cls.get_cpu_architecture()
return (cls.supports_v1(model_config) and arch
in (CpuArchEnum.X86, CpuArchEnum.POWERPC, CpuArchEnum.ARM))
return (cls.supports_v1(model_config)
and arch in (CpuArchEnum.X86, CpuArchEnum.POWERPC,
CpuArchEnum.ARM, CpuArchEnum.S390X))

3
vllm/platforms/interface.py
View File

@ -81,6 +81,7 @@ class CpuArchEnum(enum.Enum):
X86 = enum.auto()
ARM = enum.auto()
POWERPC = enum.auto()
S390X = enum.auto()
OTHER = enum.auto()
UNKNOWN = enum.auto()
@ -377,6 +378,8 @@ class Platform:
return CpuArchEnum.ARM
elif machine.startswith("ppc"):
return CpuArchEnum.POWERPC
elif machine == "s390x":
return CpuArchEnum.S390X
return CpuArchEnum.OTHER if machine else CpuArchEnum.UNKNOWN

5
vllm/v1/worker/cpu_worker.py
View File

@ -43,8 +43,9 @@ class CPUWorker(Worker):
# Setup OpenMP threads affinity.
omp_cpuids = envs.VLLM_CPU_OMP_THREADS_BIND
if omp_cpuids == "auto" and platform.system() == "Linux":
if current_platform.get_cpu_architecture() == CpuArchEnum.POWERPC:
# For POWERPC SMT-8/4/2
cpu_arch = current_platform.get_cpu_architecture()
if cpu_arch in (CpuArchEnum.POWERPC, CpuArchEnum.S390X):
# For S390X/POWERPC SMT-8/4/2
self.local_omp_cpuid = self._get_autobind_cpu_ids(
lambda cpus: [cpu for cpu in cpus if cpu.id % 8 < 4])
elif current_platform.get_cpu_architecture() == CpuArchEnum.X86: