Accelerators for Technical Computing?

Dieter an Mey, RWTH Aachen

13 Nov 2013, 16:30–18:00; Location: S4|10-1

“More bang for the buck” is the promise of deploying accelerators attached to commodity host processors for technical computing. Since NVIDIA introduced the CUDA programming model in 2006, more and more programmers started using graphics processors for technical computing. Amazing success stories reported high speed-up rates of applications accelerated by GPUs. But programmers had to find out that GPUs are not particularly easy to program using CUDA and portability is lost. New programming approaches promising to increase programmability and/or portability are published more frequently than any user may want to adapt his or her program code: OpenCL, PGI Accelerator, Open ACC and finally OpenMP 4.0. After Larrabee was cancelled in 2009 it took Intel until 2012 to come up with a competing product with the promise to combine performance, portability and programmability: the Xeon Phi coprocessor. We take a holistic view on the deployment of accelerators which are already part of over 10% of the world’s fastest computers listed the last Top500 list.

Category: CE Seminar


Technische Universität Darmstadt

Graduate School CE
Dolivostraße 15
D-64293 Darmstadt

Phone+49 6151/16-24401
Fax -24404

to assistants' office

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