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Toward a new metric for ranking high performance computing systems

Heroux, Michael A.

The High Performance Linpack (HPL), or Top 500, benchmark [1] is the most widely recognized and discussed metric for ranking high performance computing systems. However, HPL is increasingly unreliable as a true measure of system performance for a growing collection of important science and engineering applications. In this paper we describe a new high performance conjugate gradient (HPCG) benchmark. HPCG is composed of computations and data access patterns more commonly found in applications. Using HPCG we strive for a better correlation to real scientific application performance and expect to drive computer system design and implementation in directions that will better impact performance improvement.

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TYPE SAND Report YEAR 2013
DOIOSTI

Designing experiments through compressed sensing

Young, Joseph G.; Ridzal, Denis R.

In the following paper, we discuss how to design an ensemble of experiments through the use of compressed sensing. Specifically, we show how to conduct a small number of physical experiments and then use compressed sensing to reconstruct a larger set of data. In order to accomplish this, we organize our results into four sections. We begin by extending the theory of compressed sensing to a finite product of Hilbert spaces. Then, we show how these results apply to experiment design. Next, we develop an efficient reconstruction algorithm that allows us to reconstruct experimental data projected onto a finite element basis. Finally, we verify our approach with two computational experiments.

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TYPE SAND Report YEAR 2013
DOIOSTI
Results 6601–6625 of 9,998
Results 6601–6625 of 9,998