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SCHEDULE: NOV 16-21, 2014
When viewing the Technical Program schedule, on the far righthand side is a column labeled "PLANNER." Use this planner to build your own schedule. Once you select an event and want to add it to your personal schedule, just click on the calendar icon of your choice (outlook calendar, ical calendar or google calendar) and that event will be stored there. As you select events in this manner, you will have your own schedule to guide you through the week.
GPU Acceleration of Small Dense Matrix Computation of the One-Sided Factorizations
SESSION: Poster Reception
EVENT TYPE: Posters
TIME: 5:15PM - 7:00PM
AUTHOR(S):Tingxing Dong, Mark Gates, Azzam Haidar, Piotr Luszczek, Stanimire Tomov
ROOM:New Orleans Theater Lobby
ABSTRACT:
In scientific of applications, one often needs to solve many small size problems. The size of each of these small linear systems depends, for example, on the number of the ordinary differential equations (ODEs) used in the model, and can be on the order of hundreds of unknowns. To efficiently exploit the computing power of modern accelerator hardware, these linear systems are processed in batches.The state-of-the-art libraries for linear algebra that target GPUs, such as MAGMA, focus on large matrix sizes. They change the data layout by transposing the matrix to avoid these divergence and non-coalescing penalties. However, the data movement associated with transposition is very expensive for small matrices. We propose a batched one-sided factorizations for GPUs by using a multi-level blocked right looking algorithm that preserves the data layout but minimizes the penalty of partial pivoting. Our implementation achieves many-fold speedup when compared to the alternatives.
Chair/Author Details:
Tingxing Dong - University of Tennessee, Knoxville
Mark Gates - University of Tennessee, Knoxville
Azzam Haidar - University of Tennessee, Knoxville
Piotr Luszczek - University of Tennessee, Knoxville
Stanimire Tomov - University of Tennessee, Knoxville
Click here to download .ics calendar file
