Samuel Williams

TL;DR: The parallel landscape is frame with seven questions, and the following are recommended to explore the design space rapidly: • The overarching goal should be to make it easy to write programs that execute efficiently on highly parallel computing systems • The target should be 1000s of cores per chip, as these chips are built from processing elements that are the most efficient in MIPS (Million Instructions per Second) per watt, MIPS per area of silicon, and MIPS each development dollar.

TL;DR: The Roofline model offers insight on how to improve the performance of software and hardware in the rapidly changing world of connected devices.

TL;DR: This work explores multicore stencil (nearest-neighbor) computations --- a class of algorithms at the heart of many structured grid codes, including PDF solvers, and develops a number of effective optimization strategies, and builds an auto-tuning environment that searches over these strategies to minimize runtime, while maximizing performance portability.

TL;DR: This work examines sparse matrix-vector multiply (SpMV) - one of the most heavily used kernels in scientific computing - across a broad spectrum of multicore designs, and presents several optimization strategies especially effective for the multicore environment.

TL;DR: This work examines sparse matrix-vector multiply (SpMV) - one of the most heavily used kernels in scientific computing - across a broad spectrum of multicore designs, and presents several optimization strategies especially effective for the multicore environment.