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another reuse gpu approach #15

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@jikunshang jikunshang commented Jun 25, 2025 •
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@jikunshang jikunshang changed the base branch from kunshang/xpu_v1_flash_attn to main June 25, 2025 14:29
@jikunshang jikunshang changed the base branch from main to deepseek_r1_4merge June 25, 2025 14:30
@jikunshang jikunshang changed the base branch from deepseek_r1_4merge to main June 25, 2025 14:30
@jikunshang jikunshang force-pushed the kunshang/reuse_gpu_0625 branch from 5133079 to d9e76cb Compare June 27, 2025 05:22
@jikunshang jikunshang changed the base branch from main to deepseek_r1_4merge June 27, 2025 05:23
@jikunshang jikunshang changed the base branch from deepseek_r1_4merge to main June 27, 2025 05:23
@jikunshang
another approach
e8d0d5f 
Signed-off-by: Kunshang Ji <[email protected]>
@jikunshang
remove xpu worker/runner
d9e76cb 
Signed-off-by: Kunshang Ji <[email protected]>
gujinghui
gujinghui reviewed Jul 3, 2025
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vllm/platforms/xpu.py
@@ -30,6 +30,7 @@ class XPUPlatform(Platform):
# see https://github.com/ray-project/ray/blob/6a5eb5865eeb9ccf058a79b44f107e327e360673/python/ray/_private/accelerators/intel_gpu.py#L20 # noqa: E501
ray_device_key: str = "GPU"
device_control_env_var: str = "ONEAPI_DEVICE_SELECTOR"
dist_backend: str = "ccl"
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ccl is the old backend. we'd better to use xccl as new backend for xpu.

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we will switch to xccl when torch 2.8 released. we didn't verify much xccl functionality/performance on 2.7.

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