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UID:pretalx-euroscipy-2026-VPYLDF@pretalx.com
DTSTART;TZID=CET:20260720T121000
DTEND;TZID=CET:20260720T123000
DESCRIPTION:Your GPU is fast\, so why does your Python code still feel slow
 ? This talk shows a practical\, Python-first profiling workflow with Nsigh
 t Systems\, Nsight Compute\, and NVTX for CuPy\, Numba\, PyTorch\, JAX\, a
 nd CUDA extensions. We will use timelines to find launch overhead\, hidden
  synchronizations\, and host-device copies\, then drill into kernel bottle
 necks like memory throughput and occupancy. You will leave with a repeatab
 le loop for turning profiles into measurable speedups.
DTSTAMP:20260603T201611Z
LOCATION:Room 2.41 (First Floor\, Turing)
SUMMARY:Profiling Python GPU Code - Bryce Adelstein Lelbach
URL:https://pretalx.com/euroscipy-2026/talk/VPYLDF/
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