Optimal Kernel Tuning Parameter Prediction using Deep Sequence Models

arXiv:2404.10162v1 Announce Type: new
Abstract: GPU kernels have come to the forefront of comput- ing due to their utility in varied fields, from high-performance computing to machine learning. A typical GPU compute kernel is invoked millions, if not billions of times in a typical application, which makes their performance highly critical. Due to the unknown nature of the optimization surface, an exhaustive search is required to discover the global optimum, which is infeasible due to the possible exponential number of …

abstract application arxiv compute computing cs.ai cs.lg fields gpu ing kernel machine machine learning performance prediction type utility