Stencil Computation Optimization and Auto-tuning on State-of-the-Art Multicore Architectures

Understanding the most efficient design and utilization of emerging multicore systems is one of the most chal-lenging questions faced by the mainstream and scientific computing industries in several decades. Our work ex-plores multicore stencil (nearest-neighbor) computations — a class of algorithms at the heart of many structured grid codes, including PDE solvers. We develop a number of effective optimization strategies, and build an auto-tuning environment that searches over our optimizations and their parameters to minimize runtime, while maximizing performance portability. To evaluate the effectiveness of these strategies we explore the broadest set of multicore architectures in the current HPC literature, including th