High-performance Sobel edge detection using CUDA with CPU vs GPU benchmarking, roofline analysis, and Nsight profiling.
CLI wrapper and Claude Code / Codex skill for NVIDIA Nsight Graphics 2026.1+ — capture GPU frames, export GPU Trace, and drill into bottlenecks via compact JSON.
CUDA Samples and Nsight Guided Profiling Samples
🎬 Explore GPU training efficiency with FP32 vs FP16 in this modular lab, utilizing Tensor Core acceleration for deep learning insights.
Quantum workload planning and profiler-backed architecture analysis for exact tensor-network execution.
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.
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