Topping the GPU MODE Kernel Leaderboard with NVIDIA cuda.compute
Mirrored from NVIDIA Developer Blog for archival readability. Support the source by reading on the original site.
Python dominates machine learning for its ergonomics, but writing truly fast GPU code has historically meant dropping into C++ to write custom kernels and to...
Python dominates machine learning for its ergonomics, but writing truly fast GPU code has historically meant dropping into C++ to write custom kernels and to maintain bindings back to Python. For most Python developers and researchers, this is a significant barrier to entry. Frameworks like PyTorch address this by implementing kernels in CUDA C++—either handwritten or by leveraging libraries…
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