Datacenter Energy Optimized Power Profiles
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866911303233175552 |
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| author | Narayanaswamy, Sreedhar Patel, Pratikkumar Dilipkumar Karlin, Ian Gupta, Apoorv Saripalli, Sudhir Guo, Janey |
| author_facet | Narayanaswamy, Sreedhar Patel, Pratikkumar Dilipkumar Karlin, Ian Gupta, Apoorv Saripalli, Sudhir Guo, Janey |
| contents | This paper presents datacenter power profiles, a new NVIDIA software feature released with Blackwell B200, aimed at improving energy efficiency and/or performance. The initial feature provides coarse-grain user control for HPC and AI workloads leveraging hardware and software innovations for intelligent power management and domain knowledge of HPC and AI workloads. The resulting workload-aware optimization recipes maximize computational throughput while operating within strict facility power constraints. The phase-1 Blackwell implementation achieves up to 15% energy savings while maintaining performance levels above 97% for critical applications, enabling an overall throughput increase of up to 13% in a power-constrained facility.
KEYWORDS GPU power management, energy efficiency, power profile, HPC optimization, Max-Q, Blackwell architecture |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_03872 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Datacenter Energy Optimized Power Profiles Narayanaswamy, Sreedhar Patel, Pratikkumar Dilipkumar Karlin, Ian Gupta, Apoorv Saripalli, Sudhir Guo, Janey Distributed, Parallel, and Cluster Computing This paper presents datacenter power profiles, a new NVIDIA software feature released with Blackwell B200, aimed at improving energy efficiency and/or performance. The initial feature provides coarse-grain user control for HPC and AI workloads leveraging hardware and software innovations for intelligent power management and domain knowledge of HPC and AI workloads. The resulting workload-aware optimization recipes maximize computational throughput while operating within strict facility power constraints. The phase-1 Blackwell implementation achieves up to 15% energy savings while maintaining performance levels above 97% for critical applications, enabling an overall throughput increase of up to 13% in a power-constrained facility. KEYWORDS GPU power management, energy efficiency, power profile, HPC optimization, Max-Q, Blackwell architecture |
| title | Datacenter Energy Optimized Power Profiles |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2510.03872 |