Paper Info
Title
A generic high-performance method for deinterleaving scientific data
Abstract
High-performance and energy-efficient data management applications are a necessity for HPC systems due to the extreme scale of data produced by high fidelity scientific simulations that these systems support. Data layout in memory hugely impacts the performance. For better performance, most simulations interleave variables in memory during their calculation phase, but deinterleave the data for subsequent storage and analysis. As a result, efficient data deinterleaving is critical; yet, common deinterleaving methods provide inefficient throughput and energy performance. To address this problem, we propose a deinterleaving method that is high performance, energy efficient, and generic to any data type. To the best of our knowledge, this is the first deinterleaving method that 1) exploits data cache prefetching, 2) reduces memory accesses, and 3) optimizes the use of complete cache line writes. When evaluated against conventional deinterleaving methods on 105 STREAM standard micro-benchmarks, our method always improved throughput and throughput/watt on multi-core systems. In the best case, our deinterleaving method improved throughput up to 26.2x and throughput/watt up to 7.8x.
Year
DOI
Venue
2013
10.1007/978-3-642-40047-6_58
international conference on parallel processing
Keywords
DocType
Volume
efficient data deinterleaving,exploits data,data type,deinterleaving method,energy-efficient data management application,generic high-performance method,conventional deinterleaving method,improved throughput,data layout,scientific data,inefficient throughput,common deinterleaving method
Conference
8097
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
17
6
Name
Order
Citations
PageRank
Eric R. Schendel1615.02
Steve Harenberg2175.11
Houjun Tang35315.97
Venkatram Vishwanath450747.27
Michael E. Papka5953138.69
Nagiza F. Samatova686174.04