On Sunday, May 12, the brand-new tutorial “Performance Engineering for Linear Solvers” will be presented at ISC High Performance in Hamburg by Christie Alappat (still a PhD student at FAU but now working for Intel), Jonas Thies (TU Delft), Hartwig Anzt (TU München Campus Heilbronn), and myself.

This tutorial was in the making for a long time; many concepts were made, re-made, and updated again. We aimed at a slightly higher abstraction level than in our popular tutorial “Node-Level Performance Engineering,” which has a strong focus on the Roofline model and the optimization of simple loops and loop nests. In contrast, the new tutorial concentrates on the performance of sparse linear solvers, which includes a coverage of sparse matrix-vector multiplication (SpMV), preconditioners, and even cache blocking of matrix powers via RACE, Christie’s Recursive Algebraic Coloring Engine. Since the tutorial was accepted as a half-day event, we could only accommodate online demos instead of hands-on exercises for attendees. However, all code (mostly python/numba) is available for download.