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Issue No. 04 - April (2008 vol. 41)
ISSN: 0018-9162
pp: 60-68
Jonathan Cohen , Lawrence Livermore National Laboratory
Arpith Jacob , Washington University in St. Louis
Maya Gokhale , Lawrence Livermore National Laboratory
Roger Pearce , Texas A&M University
Andy Yoo , Lawrence Livermore National Laboratory
Craig Ulmer , Sandia National Laboratories
W. Marcus Miller , Lawrence Livermore National Laboratory
ABSTRACT
Data-intensive problems challenge conventional computing architectures with demanding CPU, memory, and I/O requirements. Experiments with three benchmarks suggest that emerging hardware technologies can significantly boost performance of a wide range of applications by increasing compute cycles and bandwidth and reducing latency.
INDEX TERMS
data management, data science, GPUs, FPGAs, solid-state storage, semantic graphs, image resampling, language analysis, computer systems, data-intensive computing
CITATION
Jonathan Cohen, Arpith Jacob, Maya Gokhale, Roger Pearce, Andy Yoo, Craig Ulmer, W. Marcus Miller, "Hardware Technologies for High-Performance Data-Intensive Computing", Computer, vol. 41, no. , pp. 60-68, April 2008, doi:10.1109/MC.2008.125
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