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Hardware Technologies for High-Performance Data-Intensive Computing
April 2008 (vol. 41 no. 4)
pp. 60-68
ASCII Text
x 
 
Maya Gokhale, Jonathan Cohen, Andy Yoo, W. Marcus Miller, Arpith Jacob, Craig Ulmer, Roger Pearce, "Hardware Technologies for High-Performance Data-Intensive Computing," Computer, vol. 41, no. 4, pp. 60-68, April, 2008.
 
 
BibTex
x
 
@article{ 10.1109/MC.2008.125,
author = {Maya Gokhale and Jonathan Cohen and Andy Yoo and W. Marcus Miller and Arpith Jacob and Craig Ulmer and Roger Pearce},
title = {Hardware Technologies for High-Performance Data-Intensive Computing},
journal ={Computer},
volume = {41},
number = {4},
issn = {0018-9162},
year = {2008},
pages = {60-68},
doi = {http://doi.ieeecomputersociety.org/10.1109/MC.2008.125},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - Computer
TI - Hardware Technologies for High-Performance Data-Intensive Computing
IS - 4
SN - 0018-9162
SP60
EP68
EPD - 60-68
A1 - Maya Gokhale,
A1 - Jonathan Cohen,
A1 - Andy Yoo,
A1 - W. Marcus Miller,
A1 - Arpith Jacob,
A1 - Craig Ulmer,
A1 - Roger Pearce,
PY - 2008
KW - data management
KW - data science
KW - GPUs
KW - FPGAs
KW - solid-state storage
KW - semantic graphs
KW - image resampling
KW - language analysis
KW - computer systems
KW - data-intensive computing
VL - 41
JA - Computer
ER -
 
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.

1. R. Kolb, "The Large Synoptic Survey Telescope (LSST)," white paper, LSST Corp., 2005; www.lsst.org/Science/docsLSST_DETF_Whitepaper.pdf .
2. E. Bertin, "SWarp v2.17.0, User's Guide," Institut d'Astrophysique &Observatoire de Paris, 7 Jan. 2008; http://terapix.iap.fr/IMG/pdfswarp.pdf.
3. W.B. Cavnar and J.M. Trenkle, "N-Gram-Based Text Categorization," Proc. 3rd Ann. Symp. Document Analysis and Information Retrieval, Univ. of Nevada, 1994, pp. 161–175.
4. B.H. Bloom, "Space/Time Trade-Offs in Hash Coding with Allowable Errors," Comm. ACM, vol. 13, no. 7, 1970, pp. 422–426.
5. C.M. Kastner et al., "HAIL: A Hardware-Accelerated Algorithm for Language Identification," Proc. 2005 Int'l Conf. Field Programmable Logic and Applications, IEEE Press, 2005, pp. 499–504.
6. R. Steinberger et al., "The JRC-Acquis: A Multilingual Aligned Parallel Corpus with 20+ Languages," Proc. 5th Int'l Conf. Language Resources and Evaluation, ELRA, 2006; http://langtech.jrc.it/Documents0605_LREC_JRC-Acquis_Steinberger-et-al.pdf .
7. A. Yoo et al., "A Scalable Distributed Parallel Breadth-First Search Algorithm on BlueGene/L," Proc. 2005 ACM/IEEE Conf. Supercomputing, IEEE CS Press, 2005, pp. 25–35.

Index Terms:
data management, data science, GPUs, FPGAs, solid-state storage, semantic graphs, image resampling, language analysis, computer systems, data-intensive computing
Citation:
Maya Gokhale, Jonathan Cohen, Andy Yoo, W. Marcus Miller, Arpith Jacob, Craig Ulmer, Roger Pearce, "Hardware Technologies for High-Performance Data-Intensive Computing," Computer, vol. 41, no. 4, pp. 60-68, Apr. 2008, doi:10.1109/MC.2008.125
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