### What this PR does / why we need it?
This PR adds comprehensive documentation for the CPU binding feature on
Ascend NPUs. It includes:
- A detailed developer guide
(`docs/source/developer_guide/feature_guide/cpu_binding.md`) covering
the design, internal logic, allocation examples, and troubleshooting for
the CPU binding mechanism.
- A concise user guide
(`docs/source/user_guide/feature_guide/cpu_binding.md`) explaining the
core concepts, usage, and common issues for end-users.
- An update to `additional_config.md` to use consistent terminology for
binding strategies (`global-slicing` and `topo-affinity`).
This documentation is needed to help both developers and users
understand, use, and debug the CPU binding feature, which is critical
for performance on ARM+Ascend platforms.
### Does this PR introduce _any_ user-facing change?
No. This is a documentation-only update.
### How was this patch tested?
The documentation has been reviewed for clarity and technical accuracy.
The examples and descriptions align with the implementation in
`vllm_ascend/cpu_binding.py`.
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
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Signed-off-by: chenchuw886 <chenchuw@huawei.com>
Signed-off-by: c00818886 <chenchuwei@huawei.com>
Co-authored-by: chenchuw886 <chenchuw@huawei.com>
### What this PR does / why we need it?
As part of the preparation work for the
[RFC](https://github.com/vllm-project/vllm-ascend/issues/6214)
We have added a documentation about npugraph_ex, which mainly explains
and introduces its usage and FX graph optimization.
The introduction to FX graph optimization also includes specific
explanations of the default passes, the implementation methods for
custom fusion passes, and how to capture the FX graph during the
optimization process through environment variable configuration.
---------
Signed-off-by: chencangtao <chencangtao@huawei.com>
Co-authored-by: chencangtao <chencangtao@huawei.com>
### What this PR does / why we need it?
1. Refactor eagle and mtp function: load_model and generate_token_ids
2. Remove redundant code in mtp and eagle file
3. Refactor the UT of file
2/N of Refactor and merge mtp and eagle
Relational RFC: https://github.com/vllm-project/vllm-ascend/issues/5467
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
ut and tests
- vLLM version: release/v0.13.0
- vLLM main:
81786c8774
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Signed-off-by: lilinsiman <lilinsiman@gmail.com>
### What this PR does / why we need it?
This PR makes the following modifications:
1.delete the `user_guide/feature_guide/quantization-llm-compressor.md`
and merge it into `user_guide/feature_guide/quantization.md`.
2.update the content of `user_guide/feature_guide/quantization.md`.
3.add guidance `developer_guide/feature_guide/quantization.md' on the
adaptation of quantization algorithms and quantized models.
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
7157596103
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Signed-off-by: IncSec <1790766300@qq.com>
Signed-off-by: InSec <1790766300@qq.com>
### What this PR does / why we need it?
add developer guide for PCP&DCP
- vLLM version: release/v0.13.0
- vLLM main:
bc0a5a0c08
Signed-off-by: QiuChunshuo <qiuchunshuo@huawei.com>
### What this PR does / why we need it?
This PR introduces support for adding custom CANN `aclnn` ops to
`vllm-ascend`, allowing users to define and use their own custom
operators.
Key changes include:
- Building and installing custom ops into the `vllm-ascend`-specified
directory
- Binding the `aclnn` op interface to the `torch.ops._C_ascend` module
- Enabling invocation of these ops within `vllm-ascend`
This PR includes a sample custom op:
`aclnnGroupedMatmulSwigluQuantWeightNzTensorList`, which is adapted from
the CANN operator
[`aclnnGroupedMatmulSwigluQuantWeightNZ`](https://www.hiascend.com/document/detail/zh/canncommercial/83RC1/API/aolapi/context/aclnnGroupedMatmulSwigluQuantWeightNZ.md).
Its input parameters `weight` and `weight_scale` now accept
`list[torch.Tensor]` (i.e., `at::TensorList`).
### Does this PR introduce _any_ user-facing change?
No.
- vLLM version: v0.11.2
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Signed-off-by: QianChenxi <chenxi.qian.cq@outlook.com>
### What this PR does / why we need it?
Add developer guide of eplb
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
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Signed-off-by: offline0806 <3337230449@qq.com>
Co-authored-by: offline0806 <3337230449@qq.com>
### What this PR does / why we need it?
Add aclgraph developer guide.
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: zzzzwwjj <1183291235@qq.com>
### What this PR does / why we need it?
To help more developers quickly get started with vLLM, we need to write
clear and easy-to-understand code documentation and technical
interpretations. This will effectively lower the learning curve, attract
more excellent contributors, and collectively build a better developer
community.
Add ModelRunner_prepare_inputs doc
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
Pass CI
- vLLM version: v0.10.0
- vLLM main:
4be02a3776
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Signed-off-by: ChenTaoyu-SJTU <ctynb@qq.com>
1. Format the developer guide content to make it more clear
2. Add the patch doc for developer guide
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
