linfeng-yuan 90a75a90a9 [bugfix] fix torchair runtime error caused by configuration mismtaches and file missing (#2532)
### What this PR does / why we need it?
This PR ports #2312 #2506 #2531 to main branch.

Original implementation of torchair caching forces users to make
everything prepared, fix all the configuration and enable
`use_cached_npu_graph`, and it might cause some problems confusing to
understand and tackle for users. It is better to compile the graph twice
instead of reusing the old kvcaches and cached torchair graph. And the
extra duration time is acceptable. Additionally, this pr fixes a
recompilation problem of torchair graph mode caused by
`running_in_graph` variable in `AscendMLATorchairImpl`.

### Does this PR introduce _any_ user-facing change?
If users want to enabling torchair.cache_compile with high compilation
speed, it is recommended to enable both `use_cached_kv_cache_bytes` and
`use_cached_graph` in `torchair_graph_config`. Without
`use_cached_kv_cache_bytes`, we'll compile torchair computation graph
twice to avoid runtime error caused by configuration mismtaches (the
second compilation will be much faster). Additionally, we've made a
change to how the TORCHAIR_CACHE_HOME enviroment variable is utilized to
enhance safety and prevent accidental file deletion by adding a suffix
directory.

### How was this patch tested?
CI and e2e vllm serving pass.


- vLLM version: v0.10.1.1
- vLLM main:
70549c1245

---------

Signed-off-by: linfeng-yuan <1102311262@qq.com>
2025-09-03 17:56:12 +08:00
2025-08-11 22:21:29 +08:00
2025-09-03 15:53:50 +08:00
2025-09-01 15:49:07 +08:00
2025-02-05 10:53:12 +08:00
2025-08-22 07:30:48 +08:00
2025-08-22 07:30:48 +08:00
2025-08-22 07:30:48 +08:00
2025-01-29 02:44:13 -08:00
2025-08-11 11:22:32 +08:00
2025-08-25 11:39:29 +08:00
2025-08-11 11:22:32 +08:00

vllm-ascend

vLLM Ascend Plugin

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Latest News 🔥

  • [2025/06] User stories page is now live! It kicks off with LLaMA-Factory/verl//TRL/GPUStack to demonstrate how vLLM Ascend assists Ascend users in enhancing their experience across fine-tuning, evaluation, reinforcement learning (RL), and deployment scenarios.
  • [2025/06] Contributors page is now live! All contributions deserve to be recorded, thanks for all contributors.
  • [2025/05] We've released first official version v0.7.3! We collaborated with the vLLM community to publish a blog post sharing our practice: Introducing vLLM Hardware Plugin, Best Practice from Ascend NPU.
  • [2025/03] We hosted the vLLM Beijing Meetup with vLLM team! Please find the meetup slides here.
  • [2025/02] vLLM community officially created vllm-project/vllm-ascend repo for running vLLM seamlessly on the Ascend NPU.
  • [2024/12] We are working with the vLLM community to support [RFC]: Hardware pluggable.

Overview

vLLM Ascend (vllm-ascend) is a community maintained hardware plugin for running vLLM seamlessly on the Ascend NPU.

It is the recommended approach for supporting the Ascend backend within the vLLM community. It adheres to the principles outlined in the [RFC]: Hardware pluggable, providing a hardware-pluggable interface that decouples the integration of the Ascend NPU with vLLM.

By using vLLM Ascend plugin, popular open-source models, including Transformer-like, Mixture-of-Expert, Embedding, Multi-modal LLMs can run seamlessly on the Ascend NPU.

Prerequisites

  • Hardware: Atlas 800I A2 Inference series, Atlas A2 Training series, Atlas 800I A3 Inference series, Atlas A3 Training series, Atlas 300I Duo (Experimental)
  • OS: Linux
  • Software:
    • Python >= 3.9, < 3.12
    • CANN >= 8.2.rc1
    • PyTorch >= 2.7.1, torch-npu >= 2.7.1.dev20250724
    • vLLM (the same version as vllm-ascend)

Getting Started

Please use the following recommended versions to get started quickly:

Version Release type Doc
v0.10.0rc1 Latest release candidate QuickStart and Installation for more details
v0.9.1rc3 Next stable release QuickStart and Installation for more details
v0.7.3.post1 Latest stable version QuickStart and Installation for more details

Contributing

See CONTRIBUTING for more details, which is a step-by-step guide to help you set up development environment, build and test.

We welcome and value any contributions and collaborations:

Branch

vllm-ascend has main branch and dev branch.

  • main: main branchcorresponds to the vLLM main branch, and is continuously monitored for quality through Ascend CI.
  • vX.Y.Z-dev: development branch, created with part of new releases of vLLM. For example, v0.7.3-dev is the dev branch for vLLM v0.7.3 version.

Below is maintained branches:

Branch Status Note
main Maintained CI commitment for vLLM main branch and vLLM 0.10.x branch
v0.7.1-dev Unmaintained Only doc fixed is allowed
v0.7.3-dev Maintained CI commitment for vLLM 0.7.3 version, only bug fix is allowed and no new release tag any more.
v0.9.1-dev Maintained CI commitment for vLLM 0.9.1 version
rfc/feature-name Maintained Feature branches for collaboration

Please refer to Versioning policy for more details.

Weekly Meeting

License

Apache License 2.0, as found in the LICENSE file.

Description
XC-LLM: A Specially Optimized LLM Inference Engine for ModelHub XC
Readme Apache-2.0 8.6 MiB
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