Online auto-tuning for the time-step-based parallel solution of ODEs on shared-memory systems
Online auto-tuning approach suited to time stepping nature of (parallel) ODE solvers. Model-driven empirical tile size selection integrated into the auto-tuning approach. Reduction of search space of code variants by estimating synchronization overhead. Shared-memory implementation for a class of explicit PC methods of RK type. Detailed experimental evaluation on different architectures.
auto-tuning parallelization tile size selection ordinary differential equations predictorcorrector methods