Re: [PATCH] mm: limit THP alignment – performance gain observed in AI inference workloads

[siddhartha@kenip.in]

> Hi all,
> 
> I wanted to share validation data from a Hugging Face-based AI
> inferencing workload,
> which was significantly impacted by the THP alignment logic introduced
> in commit efa7df3e3bb5.
> 
> Using transformer models with dynamic input lengths on Intel Xeon 
> (Cooper Lake),
> we observed up to a 3200% throughput improvement after applying the
> patch from Oct 2024:
> 
>   mm: limit THP alignment of anonymous mappings to PMD-aligned sizes
> 
> Metrics:
> - Model: BERT-base
> - Inference engine: Transformers + ONNX Runtime
> - Kernel: 6.6 vs patched 6.6.8
> - Batch size: 8-32, input length: 64-512 tokens
> - Metric: inference throughput (samples/sec)
> 
> Thanks for the fix -- this change had real impact on a
> production-relevant workload.
> 
> Best Regards,
> Siddhartha Sharma
> ISV @ Kenip
> Solution Link:
> https://www.intel.com/content/www/us/en/partner/showcase/offering/a5bHo00000045YUIAY/deadlock-clearance.html