Quantifying the common computational problems in contemporary applications.
Jongerius, R.; Stanley-Marbell, P.; and Corporaal, H.
In
Proceedings of the 2011 IEEE International Symposium on Workload Characterization, IISWC 2011, Austin, TX, USA, November 6-8, 2011, pages 74, 2011. IEEE Computer Society
Paper
doi
link
bibtex
6 downloads
@inproceedings{DBLP:conf/iiswc/JongeriusSC11,
author = {Rik Jongerius and
Phillip Stanley{-}Marbell and
Henk Corporaal},
title = {Quantifying the common computational problems in contemporary applications},
booktitle = {Proceedings of the 2011 {IEEE} International Symposium on Workload
Characterization, {IISWC} 2011, Austin, TX, USA, November 6-8, 2011},
pages = {74},
publisher = {{IEEE} Computer Society},
year = {2011},
url = {https://doi.org/10.1109/IISWC.2011.6114199},
doi = {10.1109/IISWC.2011.6114199},
timestamp = {Fri, 24 Mar 2023 00:00:00 +0100},
biburl = {https://dblp.org/rec/conf/iiswc/JongeriusSC11.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Pinned to the walls: impact of packaging and application properties on the memory and power walls.
Stanley-Marbell, P.; Cabezas, V. C.; and Luijten, R. P.
In Chang, N.; Nakamura, H.; Inoue, K.; Osada, K.; and Poncino, M., editor(s),
Proceedings of the 2011 International Symposium on Low Power Electronics and Design, 2011, Fukuoka, Japan, August 1-3, 2011, pages 51–56, 2011. IEEE/ACM
Paper
link
bibtex
6 downloads
@inproceedings{DBLP:conf/islped/Stanley-MarbellCL11,
author = {Phillip Stanley{-}Marbell and
Victoria Caparr{\'{o}}s Cabezas and
Ronald P. Luijten},
editor = {Naehyuck Chang and
Hiroshi Nakamura and
Koji Inoue and
Kenichi Osada and
Massimo Poncino},
title = {Pinned to the walls: impact of packaging and application properties
on the memory and power walls},
booktitle = {Proceedings of the 2011 International Symposium on Low Power Electronics
and Design, 2011, Fukuoka, Japan, August 1-3, 2011},
pages = {51--56},
publisher = {{IEEE/ACM}},
year = {2011},
url = {http://portal.acm.org/citation.cfm?id=2016815\&\#38;CFID=34981777\&\#38;CFTOKEN=25607807},
timestamp = {Mon, 13 Aug 2012 09:40:34 +0200},
biburl = {https://dblp.org/rec/conf/islped/Stanley-MarbellCL11.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Quantitative analysis of parallelism and data movement properties across the Berkeley computational motifs.
Cabezas, V. C.; and Stanley-Marbell, P.
In Cascaval, C.; Trancoso, P.; and Prasanna, V. K., editor(s),
Proceedings of the 8th Conference on Computing Frontiers, 2011, Ischia, Italy, May 3-5, 2011, pages 17, 2011. ACM
Paper
doi
link
bibtex
6 downloads
@inproceedings{DBLP:conf/cf/CabezasS11,
author = {Victoria Caparr{\'{o}}s Cabezas and
Phillip Stanley{-}Marbell},
editor = {Calin Cascaval and
Pedro Trancoso and
Viktor K. Prasanna},
title = {Quantitative analysis of parallelism and data movement properties
across the Berkeley computational motifs},
booktitle = {Proceedings of the 8th Conference on Computing Frontiers, 2011, Ischia,
Italy, May 3-5, 2011},
pages = {17},
publisher = {{ACM}},
year = {2011},
url = {https://doi.org/10.1145/2016604.2016625},
doi = {10.1145/2016604.2016625},
timestamp = {Tue, 06 Nov 2018 00:00:00 +0100},
biburl = {https://dblp.org/rec/conf/cf/CabezasS11.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Parallelism and Data Movement Characterization of Contemporary Application Classes.
Caparrós Cabezas, V.; and Stanley-Marbell, P.
In of
SPAA '11, pages 95–104, New York, NY, USA, 2011. Association for Computing Machinery
Paper
link
paper
doi
link
bibtex
abstract
@inproceedings{10.1145/1989493.1989506,
author = {Caparr\'{o}s Cabezas, Victoria and Stanley-Marbell, Phillip},
title = {Parallelism and Data Movement Characterization of Contemporary Application Classes},
year = {2011},
isbn = {9781450307437},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1989493.1989506},
doi = {10.1145/1989493.1989506},
pages = {95–104},
numpages = {10},
keywords = {basic-block-level parallelism, berkeley computational motifs, instruction-level parallelism, data movement},
location = {San Jose, California, USA},
series = {SPAA '11},
abstract = {This paper presents a framework for characterizing the distribution of fine-grained parallelism, data movement, and communication-minimizing code partitions. Understanding the spectrum of parallelism available in applications, and how much data movement might result if such parallelism is exploited, is essential in the hardware design process because these properties will be the limiters to performance scaling of future computing systems. The framework is applied to characterizing 26 applications and kernels, classified according to their dominant components in the Berkeley dwarf/ computational motif classification.
The distributions of ILP and TLP over execution time are studied, and it is shown that, though mean ILP is high, available ILP is significantly smaller for most of the execution. The results from this framework are complemented by hardware performance counter data on two RISC platforms (IBM Power7 and Freescale P2020) and one CISC platform (IntelAtom D510), spanning a broad range of real machine characteristics. Employing a combination of these new techniques, and building upon previous proposals, it is demonstrated that the similarity in available ideal-case parallelism and data movement within and across the dwarf classes, is limited.},
url_link = {https://dl.acm.org/doi/10.1145/1989493.1989506},
url_paper = {https://physcomp.eng.cam.ac.uk/parallelism-and-data-movement-characterization-of-contemporary-application-classes}
}
This paper presents a framework for characterizing the distribution of fine-grained parallelism, data movement, and communication-minimizing code partitions. Understanding the spectrum of parallelism available in applications, and how much data movement might result if such parallelism is exploited, is essential in the hardware design process because these properties will be the limiters to performance scaling of future computing systems. The framework is applied to characterizing 26 applications and kernels, classified according to their dominant components in the Berkeley dwarf/ computational motif classification. The distributions of ILP and TLP over execution time are studied, and it is shown that, though mean ILP is high, available ILP is significantly smaller for most of the execution. The results from this framework are complemented by hardware performance counter data on two RISC platforms (IBM Power7 and Freescale P2020) and one CISC platform (IntelAtom D510), spanning a broad range of real machine characteristics. Employing a combination of these new techniques, and building upon previous proposals, it is demonstrated that the similarity in available ideal-case parallelism and data movement within and across the dwarf classes, is limited.