Collaborative Research: Tuning Libraries to Effectively Exploit the Memory Heirarchy

Tufts University, Medford MA

Investigators

Abstract

Title: Collaborative Research: tuning libraries to effectively exploit the memory hierarchy. PI: Misha Kilmer, Tufts University co-PIs: David Kaeli and Gene Cooperman, Northeastern University Abstract: We propose to improve the performance of library codes as run on a multi-level memory hierarchy using three different approaches to optimization. We will target blocking and preconditioning methods to increase the locality of reference in sparse and structured matrices. Next we employ cache-conscious data structures to further improve memory hierarchy utilization. Finally, we perform code and data layout transformations that effectively remap library to the underlying memory hardware. Our initial target applications include a variety of Krylov iterative solvers. While we plan to produce optimized versions of these library codes, we will also pursue additional classes of libraries. Our optimizations will address the need to effectively migrate code to new hardware platforms and exploit the novel architecture features provided on the new platform.