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Issue No. 04 - April (2008 vol. 41)
ISSN: 0018-9162
pp: 60-68
Maya Gokhale , Lawrence Livermore National Laboratory
Jonathan Cohen , Lawrence Livermore National Laboratory
Andy Yoo , Lawrence Livermore National Laboratory
W. Marcus Miller , Lawrence Livermore National Laboratory
Arpith Jacob , Washington University in St. Louis
Craig Ulmer , Sandia National Laboratories
Roger Pearce , Texas A&M University
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.
data management, data science, GPUs, FPGAs, solid-state storage, semantic graphs, image resampling, language analysis, computer systems, data-intensive computing

J. Cohen et al., "Hardware Technologies for High-Performance Data-Intensive Computing," in Computer, vol. 41, no. , pp. 60-68, 2008.
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