- Home
- Register
- Attend
- Conference Program
- SC15 Schedule
- Technical Program
- Awards
- Students@SC
- Research with SCinet
- HPC Impact Showcase
- HPC Matters Plenary
- Keynote Address
- Support SC
- SC15 Archive
- Exhibits
- Media
- SCinet
- HPC Matters
SCHEDULE: NOV 15-20, 2015
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.
Linear Algebra Libraries for High-Performance Computing: Scientific Computing with Multicore and Accelerators
SESSION: Linear Algebra Libraries for High-Performance Computing: Scientific Computing with Multicore and Accelerators
EVENT TYPE: Tutorials
EVENT TAG(S): Programming Systems, Accelerators, Reconfigurable Computing, Algorithms
TIME: 8:30AM - 5:00PM
Presenter(s):Jack Dongarra, Jakub Kurzak, Michael Heroux, James Demmel
ROOM:15
ABSTRACT:
Today, a desktop with a multicore processor and a GPU accelerator can already provide a TeraFlop/s of performance, while the performance of the high-end systems, based on multicores and accelerators, is already measured in tens of PetaFlop/s. This tremendous computational power can only be fully utilized with the appropriate software infrastructure, both at the low end (desktop, server) and at the high end (supercomputer installation). Most often a major part of the computational effort in scientific and engineering computing goes in solving linear algebra subproblems. After providing a historical overview of legacy software packages, the tutorial surveys the current state-of-the-art numerical libraries for solving problems in linear algebra, both dense and sparse. MAGMA, (D)PLASMA and Trilinos software packages are discussed in detail. The tutorial also highlights recent advances in algorithms that minimize communication, i.e. data motion, which is much more expensive than arithmetic.
Chair/Presenter Details:
Jack Dongarra - University of Tennessee, Knoxville
Jakub Kurzak - University of Tennessee, Knoxville
Michael Heroux - Sandia National Laboratories
James Demmel - University of California, Berkeley
Click here to download .ics calendar file
