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cuda-optimization

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jetson-orin-matmul-analysis

Cre4T3Tiv3 / jetson-orin-matmul-analysis

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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.

machine-learning robotics cuda cublas scientific-computing matrix-multiplication high-performance-computing gpu-computing performance-optimization autonomous-systems edge-computing nvidia-jetson edge-ai embeded-systems tensor-cores ml-deployment jetson-orin-nano gpu-benchmarking power-efficiency-benchmark cuda-optimization
  • Updated Oct 14, 2025
  • Python

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