Bayesian Optimization for auto-tuning GPU kernels
Bayesian Optimization for auto-tuning GPU kernels
Finding optimal parameter configurations for tunable GPU kernels is a non-trivial exercise for large search spaces, even when automated. This poses an optimization task on a nonconvex search space, using an expensive to evaluate function with unknown derivative. These characteristics make a good candidate for Bayesian Optimization, which has not …