vllm-project/vllm

[Feature]: Run performance benchmarks for multi-modal models in CI

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#16 353 ouverte le 9 avr. 2025

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 (15 commentaires) (0 réactions) (0 assignés)Python (16 816 forks)batch import
feature requesthelp wantedkeep-openmulti-modality

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Description

🚀 The feature, motivation and pitch

We currently only have benchmarks for text-only models such as Llama. With the increasing importance of multi-modality and related optimizations such as processor cache, we should add performance benchmarks for multi-modal models to avoid regressions (e.g. memory leaks, slow batching).

We can measure the peak memory usage based on this code:

import resource

max_self_usage = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss / (1 << 20)
max_children_usage = resource.getrusage(resource.RUSAGE_CHILDREN).ru_maxrss / (1 << 20)
print(f"Peak memory usage: {max_self_usage} (self) + {max_children_usage} (children) GiB")

Alternatives

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Additional context

cc @mgoin @ywang96

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