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Scientific CUDA benchmarking framework: 4 implementations x 3 power modes x 5 matrix sizes on Jetson Orin Nano. 1,282 GFLOPS peak, 90% performance @ 88% power (25W mode), 99.5% accuracy validation, edge AI deployment guide.
benchHUB is a Python-based project to parse, aggregate, and visualize system and performance benchmarks. It includes a Streamlit dashboard to display and compare results.