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UID:submissions.supercomputing.org_SC25_sess620_post270@linklings.com
SUMMARY:Towards Application Agnostic HPC Profiling
DESCRIPTION:Hari Teja Jajula (The University of Alabama, Lawrence Berkeley
  National Laboratory (LBNL)); Dhruva Kulkarni and Brian Austin (Lawrence B
 erkeley National Laboratory (LBNL)); and Purushotham Bangalore (The Univer
 sity of Alabama)\n\nModern HPC systems generate large amounts of GPU and n
 etwork telemetry, typically used for system health monitoring. At NERSC, w
 e are developing a Performance API/UI that generates a job report card fro
 m this telemetry, providing an overview of performance characteristics. Us
 ing DCGM counters, we report GPU memory, compute, and power usage, and pre
 sent preliminary investigations of job-level network activity. Without tra
 ditional profiling tools, this application-agnostic approach helps identif
 y resource utilization imbalances, detect anomalies such as memory leaks, 
 and assess overall performance for the user without additional effort.\n\n
 Tag: Research & ACM SRC Posters\n\nRegistration Category: Technical Progra
 m Reg Pass\n\nSession Chairs: Kento Sato (RIKEN Center for Computational S
 cience (R-CCS)); Anja Gerbes (Georg-August-Universität Göttingen); and Chr
 is Schlipalius (Pawsey Supercomputing Research Centre; Commonwealth Scient
 ific and Industrial Research Organisation (CSIRO), Australia)\n\n
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