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Masahiro Arakawa

dblp:44/1136 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1996
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
High-performance computing · 46% Hardware accelerators and domain-specific architectures · 23% Parallel and multicore computing · 23%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
High-performance computing
domain decomposition
0.011996
Benchmark Evaluation of the IBM SP2 for Parallel Signal Processing · IEEE Trans. Parallel Distributed Syst. 1996
Parallel and multicore computing › parallel programming models
message passing
0.011996
Benchmark Evaluation of the IBM SP2 for Parallel Signal Processing · IEEE Trans. Parallel Distributed Syst. 1996
High-performance computing › parallel numerical algorithms
parallel signal processing
0.011996
Benchmark Evaluation of the IBM SP2 for Parallel Signal Processing · IEEE Trans. Parallel Distributed Syst. 1996
Hardware accelerators and domain-specific architectures › signal processing accelerator
radar signal processing
0.011996
Benchmark Evaluation of the IBM SP2 for Parallel Signal Processing · IEEE Trans. Parallel Distributed Syst. 1996
Performance modeling and evaluation
benchmarking
0.011996
Benchmark Evaluation of the IBM SP2 for Parallel Signal Processing · IEEE Trans. Parallel Distributed Syst. 1996

Methods — techniques the papers use, named apart from their topics

message passing · 0.0collective communication optimization · 0.0
YearPublicationVenuePosition
1996 Benchmark Evaluation of the IBM SP2 for Parallel Signal Processing
abstract
This paper evaluates the IBM SP2 architecture, the AIX parallel programming environment, and the IBM message-passing library (MPL) through STAP (Space-Time Adaptive Processing) benchmark experiments. Only coarse-grain parallelism was exploited on the SP2 due to its high communication overhead. A new parallelization scheme is developed for programming message passing multicomputers. Parallel STAP benchmark structures are illustrated with domain decomposition, efficient mapping of partitioned programs, and optimization of collective communication operations. We measure the SP2 performance in terms of execution time, Gflop/s rate, speedup over a single SP2 node, and overall system utilization. With 256 nodes, the Maul SP2 demonstrated the best performance of 23 Gflop/s in executing the High-Order Post-Doppler program, corresponding to a 34% system utilization. We have conducted a scalability analysis to reveal the performance growth rate as a function of machine size and STAP problem size. Important lessons learned from these parallel processing benchmark experiments are discussed in the context of real-time, adaptive, radar signal processing on massively parallel processors (MPP).
Kai Hwang 0001, Masahiro Arakawa
IEEE Trans. Parallel Distributed Syst.3