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[XPU] upgrade to PyTorch 2.14 (#56013)

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Signed-off-by: Yan Ma <yan.ma@intel.com>
Signed-off-by: Kunshang Ji <kunshang.ji@intel.com>
Co-authored-by: Kunshang Ji <kunshang.ji@intel.com>
This commit is contained in:
Yan Ma
2026-09-23 09:18:52 +00:00
committed by GitHub
co-authored by Kunshang Ji
parent c843f0cab7
commit e34489a543
6 changed files with 66 additions and 28 deletions
Download Patch File Download Diff File Expand all files Collapse all files
.buildkite/intel_jobs/test-intel.yaml
+1 -1
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@@ -106,7 +106,7 @@ steps:
pytest -v -s v1/test_serial_utils.py &&
pytest -v -s v1/e2e/general/test_correctness_sliding_window.py &&
pytest -v -s v1/spec_decode --ignore=v1/spec_decode/test_max_len.py --ignore=v1/spec_decode/test_speculators_eagle3.py --ignore=v1/spec_decode/test_acceptance_length.py --ignore=v1/spec_decode/test_speculators_correctness.py --deselect=tests/v1/spec_decode/test_mtp.py::test_glm_mtp_defers_lm_head &&
pytest -v -s v1/kv_connector/unit --ignore=v1/kv_connector/unit/test_lmcache_integration.py --ignore=v1/kv_connector/unit/test_hf3fs_client.py --ignore=v1/kv_connector/unit/test_hf3fs_connector.py --ignore=v1/kv_connector/unit/test_hf3fs_metadata_server.py --ignore=v1/kv_connector/unit/test_offloading_connector.py --deselect "v1/kv_connector/unit/test_nixl_connector.py::test_abort_timeout_on_prefiller[ray]"'
pytest -v -s v1/kv_connector/unit --ignore=v1/kv_connector/unit/test_lmcache_integration.py --ignore=v1/kv_connector/unit/test_hf3fs_client.py --ignore=v1/kv_connector/unit/test_hf3fs_connector.py --ignore=v1/kv_connector/unit/test_hf3fs_metadata_server.py --ignore=v1/kv_connector/unit/test_offloading_connector.py --deselect "v1/kv_connector/unit/test_nixl_connector.py::test_abort_timeout_on_prefiller[ray]" --ignore=v1/kv_connector/unit/test_nixl_connector_hma.py'
parallelism: 2
- label: "XPU server test"
key: xpu-server-test
docker/Dockerfile.xpu
+18
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@@ -87,11 +87,14 @@ RUN mkdir neo && \
# Install XPU-Manager payloads without registering conflicting libze package
# dependencies in dpkg.
# Note that ocl-icd-opencl-dev is required by DLE upgrade but xpu-smi, should
# can be removed in future.
RUN apt-get update -y && \
apt-get install -y --no-install-recommends software-properties-common && \
add-apt-repository -y ppa:kobuk-team/intel-graphics && \
apt-get update -y && \
apt-get install -y --no-install-recommends libhwloc15 libpciaccess0 libigsc1 intel-metrics-library && \
apt-get install -y ocl-icd-opencl-dev && \
mkdir xpu-m && \
cd xpu-m && \
wget https://github.com/intel/xpumanager/releases/download/v2.1.0/xpu-smi_2.1.0+26.33.6468cec-1.24.04_amd64.deb && \
@@ -264,4 +267,19 @@ RUN --mount=type=cache,target=/root/.cache/uv \
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install -e tests/vllm_test_utils
# Replace 2026.1.2 DLE packages to 2026.1.3
RUN --mount=type=cache,target=/root/.cache/uv \
--mount=type=bind,source=.git,target=.git \
uv pip install \
"intel-cmplr-lib-rt==2026.1.1" \
"intel-cmplr-lib-ur==2026.1.1" \
"intel-cmplr-lic-rt==2026.1.1" \
"intel-sycl-rt==2026.1.1" \
"oneccl-devel==2022.1.2; platform_system == 'Linux' and platform_machine == 'x86_64'" \
"oneccl==2022.1.2; platform_system == 'Linux' and platform_machine == 'x86_64'" \
"dpcpp-cpp-rt==2026.1.1" \
"intel-opencl-rt==2026.1.1" \
"intel-openmp==2026.1.1" \
"intel-pti==1.1.0"
ENTRYPOINT ["vllm", "serve"]
docs/getting_started/installation/gpu.xpu.inc.md
+16
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@@ -32,6 +32,22 @@ To install the wheel built from the latest main branch:
uv pip install vllm --extra-index-url https://wheels.vllm.ai/nightly/xpu --extra-index-url https://download.pytorch.org/whl/xpu --index-strategy unsafe-best-match
```
Note that after upgrading to PyTorch 2.14, xpu graph support requires specific oneAPI packages.
```bash
uv pip install \
"intel-cmplr-lib-rt==2026.1.1" \
"intel-cmplr-lib-ur==2026.1.1" \
"intel-cmplr-lic-rt==2026.1.1" \
"intel-sycl-rt==2026.1.1" \
"oneccl-devel==2022.1.2; platform_system == 'Linux' and platform_machine == 'x86_64'" \
"oneccl==2022.1.2; platform_system == 'Linux' and platform_machine == 'x86_64'" \
"dpcpp-cpp-rt==2026.1.1" \
"intel-opencl-rt==2026.1.1" \
"intel-openmp==2026.1.1" \
"intel-pti==1.1.0"
```
#### Install specific revisions
If you want to access the wheels for previous commits (e.g. to bisect the behavior change, performance regression), you can specify the commit hash in the URL:
requirements/test/xpu.txt
+24 -24
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@@ -175,7 +175,7 @@ docopt==0.6.2
# via num2words
docstring-parser==0.18.0
# via anthropic
dpcpp-cpp-rt==2026.0.0
dpcpp-cpp-rt==2026.1.0
# via
# onemkl-sycl-blas
# onemkl-sycl-dft
@@ -328,27 +328,27 @@ idna==3.18
# yarl
ijson==3.5.1
# via -r requirements/test/../common.txt
impi-rt==2021.18.0
impi-rt==2021.18.1
# via
# oneccl
# torch
iniconfig==2.3.0
# via pytest
intel-cmplr-lib-rt==2026.0.0
intel-cmplr-lib-rt==2026.1.0
# via
# intel-sycl-rt
# torch
intel-cmplr-lib-ur==2026.0.0
intel-cmplr-lib-ur==2026.1.0
# via
# intel-openmp
# intel-sycl-rt
# torch
intel-cmplr-lic-rt==2026.0.0
intel-cmplr-lic-rt==2026.1.0
# via
# intel-opencl-rt
# intel-sycl-rt
# torch
intel-opencl-rt==2026.0.0
intel-opencl-rt==2026.1.0
# via
# dpcpp-cpp-rt
# onemkl-sycl-blas
@@ -357,14 +357,14 @@ intel-opencl-rt==2026.0.0
# onemkl-sycl-rng
# onemkl-sycl-sparse
# torch
intel-openmp==2026.0.0
intel-openmp==2026.1.0
# via
# dpcpp-cpp-rt
# mkl
# torch
intel-pti==0.17.0
intel-pti==1.0.1
# via torch
intel-sycl-rt==2026.0.0
intel-sycl-rt==2026.1.0
# via
# dpcpp-cpp-rt
# oneccl
@@ -463,7 +463,7 @@ mistral-common==1.11.7
# -c requirements/common.txt
# -r requirements/test/../common.txt
# -r requirements/test/xpu.in
mkl==2026.0.0
mkl==2026.1.0
# via
# onemkl-sycl-blas
# onemkl-sycl-dft
@@ -547,28 +547,28 @@ numpy==2.2.6
# torchvision
# transformers
# xgrammar
oneccl==2022.0.0
oneccl==2022.1.1
# via
# oneccl-devel
# torch
oneccl-devel==2022.0.0
oneccl-devel==2022.1.1
# via torch
onemkl-license==2026.0.0
onemkl-license==2026.1.0
# via
# mkl
# torch
onemkl-sycl-blas==2026.0.0
onemkl-sycl-blas==2026.1.0
# via
# onemkl-sycl-lapack
# onemkl-sycl-sparse
# torch
onemkl-sycl-dft==2026.0.0
onemkl-sycl-dft==2026.1.0
# via torch
onemkl-sycl-lapack==2026.0.0
onemkl-sycl-lapack==2026.1.0
# via torch
onemkl-sycl-rng==2026.0.0
onemkl-sycl-rng==2026.1.0
# via torch
onemkl-sycl-sparse==2026.0.0
onemkl-sycl-sparse==2026.1.0
# via torch
open-clip-torch==2.32.0
# via -r requirements/test/xpu.in
@@ -836,7 +836,7 @@ pyyaml==6.0.3
# timm
# transformers
# uvicorn
pyzes==0.1.1
pyzes==0.1.2
# via torch
pyzmq==27.1.0
# via
@@ -1007,7 +1007,7 @@ tabledata==1.3.5
# via pytablewriter
tabulate==0.10.0
# via sacrebleu
tbb==2023.0.0
tbb==2023.1.0
# via
# intel-opencl-rt
# mkl
@@ -1049,7 +1049,7 @@ tokenizers==0.23.1
# cohere
# sentence-transformers
# transformers
torch==2.13.0+xpu
torch==2.14.0+xpu
# via
# -c requirements/xpu.txt
# accelerate
@@ -1062,7 +1062,7 @@ torch==2.13.0+xpu
# timm
# torchvision
# xgrammar
torchvision==0.28.0+xpu
torchvision==0.29.0+xpu
# via
# open-clip-torch
# timm
@@ -1090,11 +1090,11 @@ transformers==5.17.0
# mteb
# sentence-transformers
# xgrammar
triton==3.7.2+xpu
triton==3.8.0+xpu
# via
# -c requirements/xpu.txt
# xgrammar
triton-xpu==3.7.2
triton-xpu==3.8.0
# via
# torch
# triton
requirements/xpu.txt
+3 -3
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@@ -1,7 +1,7 @@
# Common dependencies
-r common.txt
--extra-index-url=https://wheels.vllm.ai/xpu/
triton==3.7.2+xpu
triton==3.8.0+xpu
ray>=2.9
cmake>=3.26.1
@@ -14,10 +14,10 @@ jinja2>=3.1.6
datasets # for benchmark scripts
numba == 0.65.0 # Required for N-gram speculative decoding
--extra-index-url=https://download.pytorch.org/whl/xpu
torch==2.13.0
torch==2.14.0
torchaudio
torchvision
torchcodec >= 0.14 # Required for the torchcodec video decoding backend
auto_round_lib==0.15.0
vllm_xpu_kernels==0.1.14.1
vllm_xpu_kernels==0.1.15.4
vllm/lora/ops/triton_ops/fused_moe_lora_op.py
+4
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@@ -420,6 +420,10 @@ def _run_fused_moe_lora_one_shot(
npid = min(npid_occ, max_npid_by_budget)
npid = max(1, min(npid, max(1, N_per_slice // 128)))
# see issue: https://github.com/intel/intel-xpu-backend-for-triton/issues/8121
if current_platform.is_xpu():
npid = 1
# Robust defaults across the prefill regime (H100/H200/B200, bf16/fp16).
# NPID > 1 is the small-M / under-saturated path -- more warps help
# amortise the inner-N expand loop. ns=3 instead of 4: GB200 ncu showed