A curated resource list for GPU performance engineering, organized from CUDA fundamentals through kernel optimization, inference engines, and distributed serving.

Sources are limited to original papers, official specifications, and direct implementation work. Covers hardware-specific content for NVIDIA, AMD, TPU, and Trainium.

Topics

CUDA Programming Kernel Optimization Inference Engines Distributed Inference GPU Performance Engineering

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wafer-ai/gpu-perf-engineering-resources: A curated resource list for learning AI performance engineering, from GPU fundamentals to production inference.

github.comSaved August 25, 20269 min

wafer-ai · via GitHub

Summary

A curated resource list for GPU performance engineering, organized from CUDA fundamentals through kernel optimization, inference engines, and distributed serving.

Sources are limited to original papers, official specifications, and direct implementation work. Covers hardware-specific content for NVIDIA, AMD, TPU, and Trainium.

Topics

CUDA Programming Kernel Optimization Inference Engines Distributed Inference GPU Performance Engineering

View on GitHub All Bookmarks