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DTSTAMP:20260422T143139Z
LOCATION:B303
DTSTART;TZID=America/New_York:20241118T163000
DTEND;TZID=America/New_York:20241118T170000
UID:submissions.supercomputing.org_SC24_sess748_ws_pmbsf119@linklings.com
SUMMARY:Understanding VASP Power Profiles on NVIDIA A100 GPUs
DESCRIPTION:Zhengji Zhao, Brian Austin, Ermal Rrapaj, and Nicholas Wright 
 (Lawrence Berkeley National Laboratory (LBNL))\n\nPower is a critical limi
 ting factor in supercomputing as systems scale to exascale levels. To adva
 nce scientific computing, supercomputers must operate efficiently under li
 mited power budgets. Power-aware scheduling can help by enforcing power ma
 nagement strategies, but this requires a deep understanding of application
  power behavior, especially on modern GPU-centric supercomputers. This stu
 dy examines the power behavior of VASP, a leading HPC application, on the 
 Perlmutter A100 GPU system at NERSC. We explore how VASP’s power usage cha
 nges with various inputs and parallelism and assess its response to power 
 capping. We find that VASP’s power usage varies significantly with differe
 nt workloads, more so than with parallel concurrency. Additionally, power 
 capping GPUs to 50% of their Thermal Design Power can be applied to VASP w
 orkloads with less than a 10% performance loss.\n\nThese findings shed lig
 ht on the feasibility and effectiveness of power-aware scheduling based on
  application power profiles on HPC systems.\n\nTag: Accelerators, Modeling
  and Simulation, Performance Evaluation and/or Optimization Tools\n\nRegis
 tration Category: Workshop Reg Pass\n\nSession Chairs: Simon Hammond (Nati
 onal Nuclear Security Administration (NNSA)); Sascha Hunold (Technical Uni
 versity of Vienna); and Steven A. Wright (University of York, England)\n\n
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