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GPU cluster monitoring reveals significant underutilization opportunities

By PulseAugur Editorial · [1 sources] ·

A new research paper details findings from a fine-grained monitoring study of a university GPU cluster, revealing significant underutilization. The study, conducted over 10 days using a lightweight tool that captures metrics at 100 ms intervals, found that over 70% of jobs used less than 20% of GPU memory and 50% averaged below 5% Streaming Multiprocessor utilization. The research suggests substantial gains in GPU utilization are possible through improved job scheduling and multitasking, independent of hardware or application advancements. AI

IMPACT Highlights potential for significant efficiency gains in AI compute infrastructure through better scheduling and multitasking.

RANK_REASON Research paper detailing findings from a fine-grained monitoring study of GPU cluster utilization. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

GPU cluster monitoring reveals significant underutilization opportunities

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Research paper detailing findings from a fine-grained monitoring study of GPU cluster utilization. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Andrew Sheinberg, Samyak Gupta, Kai Li ·

    Plenty of Room in the Middle: Revealing Opportunities on a GPU Cluster via Fine-Grained Monitoring

    arXiv:2610.36329v1 Announce Type: new Abstract: GPU clusters have become essential computing resources for AI and scientific research in academia and industry. However, their high cost and growing demand often result in long queueing delays. While previous monitoring efforts have…

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