

#509: GPU Programming in Pure Python
12 snips Jun 11, 2025
Bryce Adelstein Lelbach from NVIDIA, a pioneer in programming language evolution, discusses the transformative use of GPUs in modern computing, moving beyond traditional graphics. He highlights advancements in Python SDKs that allow pure Python coding for GPU programming, making it more accessible. The conversation also delves into the evolution of ARM processors, the implications of Python 3.13's removal of the global interpreter lock, and essential algorithms for high-performance tasks, paving the way for more efficient data science and machine learning applications.
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Early Programming Via MUDs
- Bryce Adelstein Lelbach started programming by teaching himself to code a Multi-User Dungeon (MUD).
- He credits these text-based games as a pure form of gaming and an early passion for programming.
GPU Impact on Exascale Computing
- Scaling to exascale computing with CPUs alone requires millions of cores and faces failure challenges.
- GPUs lowered needed nodes dramatically, making existing distributed computing models more feasible.
ARM's Prospects in Data Centers
- ARM is likely to dominate CPUs due to software ecosystem uniformity and energy efficiency.
- ARM's success in mobile devices gives it an advantage over x86 architectures.