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Authors: Diogo Guerra, Diana Gaponcic
2023-04-19

tldr - powered by Generative AI

The presentation discusses GPU utilization and benchmarking, focusing on time slicing and Mig, and provides insights on their use cases and performance trade-offs.
  • Time slicing is useful for low priority jobs with idle time, but not suitable for latency-sensitive or performance-intensive tasks.
  • Mig enables GPU sharing but comes with a performance loss due to the reduction in streaming multiprocessors.
  • Benchmarking shows that time slicing incurs a significant performance loss when contact switching is required for long-running processes.
  • Doubling memory and bandwidth through Mig can improve performance, but losing Mig without sharing the GPU results in a performance loss for no reason.
  • Monitoring pipeline utilization can help understand user jobs and optimize GPU usage.