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Title: MATCHED FILTER COMPUTATION ON FPGA, CELL, AND GPU

Abstract

The matched filter is an important kernel in the processing of hyperspectral data. The filter enables researchers to sift useful data from instruments that span large frequency bands. In this work, they evaluate the performance of a matched filter algorithm implementation on accelerated co-processor (XD1000), the IBM Cell microprocessor, and the NVIDIA GeForce 6900 GTX GPU graphics card. They provide extensive discussion of the challenges and opportunities afforded by each platform. In particular, they explore the problems of partitioning the filter most efficiently between the host CPU and the co-processor. Using their results, they derive several performance metrics that provide the optimal solution for a variety of application situations.

Authors:
 [1];  [1];  [1]
  1. Los Alamos National Laboratory
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
OSTI Identifier:
1000495
Report Number(s):
LA-UR-07-0084
TRN: US201101%%363
DOE Contract Number:
AC52-06NA25396
Resource Type:
Conference
Resource Relation:
Conference: IEEE SYMPOSIUM ON FIELD-PROGRAMMABLE CUSTON COMPUTING MACH ; 200704 ; NAPA
Country of Publication:
United States
Language:
English
Subject:
99; ALGORITHMS; IMPLEMENTATION; KERNELS; METRICS; PERFORMANCE; PROCESSING

Citation Formats

BAKER, ZACHARY K., GOKHALE, MAYA B., and TRIPP, JUSTIN L. MATCHED FILTER COMPUTATION ON FPGA, CELL, AND GPU. United States: N. p., 2007. Web.
BAKER, ZACHARY K., GOKHALE, MAYA B., & TRIPP, JUSTIN L. MATCHED FILTER COMPUTATION ON FPGA, CELL, AND GPU. United States.
BAKER, ZACHARY K., GOKHALE, MAYA B., and TRIPP, JUSTIN L. Mon . "MATCHED FILTER COMPUTATION ON FPGA, CELL, AND GPU". United States. doi:. https://www.osti.gov/servlets/purl/1000495.
@article{osti_1000495,
title = {MATCHED FILTER COMPUTATION ON FPGA, CELL, AND GPU},
author = {BAKER, ZACHARY K. and GOKHALE, MAYA B. and TRIPP, JUSTIN L.},
abstractNote = {The matched filter is an important kernel in the processing of hyperspectral data. The filter enables researchers to sift useful data from instruments that span large frequency bands. In this work, they evaluate the performance of a matched filter algorithm implementation on accelerated co-processor (XD1000), the IBM Cell microprocessor, and the NVIDIA GeForce 6900 GTX GPU graphics card. They provide extensive discussion of the challenges and opportunities afforded by each platform. In particular, they explore the problems of partitioning the filter most efficiently between the host CPU and the co-processor. Using their results, they derive several performance metrics that provide the optimal solution for a variety of application situations.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jan 08 00:00:00 EST 2007},
month = {Mon Jan 08 00:00:00 EST 2007}
}

Conference:
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