Less is more: learning what to profile for GPU kernel optimization
The proposed AutoProfiler, a feedback-driven framework for learning a deterministic profiling tree from optimization feedback, suggests that hardware profiling should evolve from static metric collection toward profiling reasoning, making profiling itself a new dimension for improving kernel optimization.
Yi-Han Wang, Pei-Yu Liu, Run-Yu Chen et al.
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