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Dartayous / FP16-vs-FP32-A-GPU-Lab-in-Frames

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A reproducible GPU benchmarking lab that compares FP16 vs FP32 training on MNIST using PyTorch, CuPy, and Nsight profiling tools. This project blends performance engineering with cinematic storytelling—featuring NVTX-tagged training loops, fused CuPy kernels, and a profiler-driven README that narrates the GPU’s inner workings frame by frame.

performance-engineering deep-learning reproducible-research cuda pytorch fp16 cupy mixed-precision nsight gpu-benchmark nvtx fp32 tensor-core
  • Updated Sep 5, 2025
  • Python

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