sponsored byACMIEEE The International Conference for High Performance 
Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 15-20, 2015

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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

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