On 2025-07-28 16:30, Vlastimil Babka wrote:

On 7/28/25 07:41, siddhartha@kenip.in wrote:

On 2025-07-07 14:26, Vlastimil Babka wrote:
Hi Lorenzo, Dev, Mel,

I'm following up on this patch submission from earlier this month:
"[PATCH] mm: limit THP alignment – performance gain observed in AI
inference workloads."

I'm confused. That wasn't a patch submission, but reporting performance
results for my patch from late 2024? (and thanks for those!)

The patch was also already merged in late 2024:

commit d4148aeab412432bf928f311eca8a2ba52bb05df
Author: Vlastimil Babka <vbabka@suse.cz>
Date:   Thu Oct 24 17:12:29 2024 +0200

    mm, mmap: limit THP alignment of anonymous mappings to PMD-aligned sizes


So there's nothing more to do here AFAIK.

Hello Vlastimil,

Hope you are doing great!

Sorry about the late reply, my inbox made your email invisible somehow.

Thank you for the clarification — yes, I am aware that the mm, mmap: limit THP alignment of anonymous mappings to PMD-aligned sizes patch was merged in late 2024 (commit d4148aeab412432bf928f311eca8a2ba52bb05df).

The performance results I shared were generated much later because of my working setup:

• The tests were conducted on Intel Developer Cloud workloads as part of a broader benchmarking exercise involving OpenVINO-based inference pipelines.

• The specific environment, dataset, and configuration scripts were stored on an SSD that unfortunately suffered corruption. I am currently working to recover them so I can share the exact test harness and commit-specific diffs. If and when I get that access back from Intel Developer Cloud, I can surely provide all those relevant files.

Although this is not a new patch submission, I thought the numbers might still be valuable — they show notable throughput and latency changes when aligning the current behavior with OpenVINO’s large contiguous allocation preferences in certain inference scenarios.

Summary of observed improvements:

• Throughput: +7.3% average increase in model inference throughput on ResNet-50 with mixed batch sizes (64/128)

• Latency: -5.1% average reduction in P99 latency under synthetic concurrent load (10 inference streams)

• System impact: Lower minor page fault count observed during sustained load, with slightly reduced RSS fluctuation

While the merged patch improves the default alignment, our tests indicate there might be headroom for further tuning in specific HPC/AI workloads — particularly when hugepage alignment is applied selectively based on allocation size and workload profile rather than strictly PMD-aligned sizes. I was also working on specifics and pseudo diffs from the working Linux code that I can generate to send that email via git send-email.

I’d be happy to collaborate on a deeper investigation once I recover the original scripts — or I can try to replicate the environment on a fresh setup and collect new diffs for comparison.

Best regards,
Siddhartha Sharma