Abstract
Each new computing platform required software developers to analyze the algorithms over and over, each time having to answer the same two questions. Does the algorithm possess the necessary properties to meet the architectural requirements? How can the algorithm be converted so that the necessary properties can be easily reflected in parallel programs? Changes in computer architecture do not change algorithms, but this analysis had to be performed again and again when a program was ported from one generation of computers to another, largely repeating the work that had been done previously. Is it possible to do the analysis “once and for all,” describing all of the key properties of an algorithm so that all of the necessary information can be gleaned from this description any time a new architecture appears? As simple as the question sounds, answering it raises a series of other non-trivial questions. Moreover, creating a complete description of an algorithm is not a challenge, it is a large series of challenges, and some of them are discussed in the paper.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Antonov, A., Voevodin, V., Dongarra, J.: AlgoWiki: an open encyclopedia of parallel algorithmic features. Supercomput. Front. Innov. 2(1), 4–18 (2015)
Dongarra, J., Beckman, P., Moore, T., Aerts, P., Aloisio, G., Andre, J.C., Barkai, D., Berthou, J.Y., Boku, T., Braunschweig, B., et al.: The international exascale software project roadmap. Int. J. High Perform. Comput. Appl. 25(1), 3–60 (2011)
Voevodin, V.V., Voevodin. Vl.V.: Parallel Computing. BHV-Petersburg, St. Petersburg (2002). (in russian)
Computing Curricula Computer Science. http://ai.stanford.edu/users/sahami/CS2013 (2013)
Future Directions in CSE Education and Research, Workshop Sponsored by the Society for Industrial and Applied Mathematics (SIAM) and the European Exascale Software Initiative (EESI-2), http://wiki.siam.org/siag-cse/images/siag-cse/f/ff/CSE-report-draft-Mar2015.pdf (2015)
NSF/IEEE-TCPP Curriculum Initiative on Parallel and Distributed Computing. http://www.cs.gsu.edu/~tcpp/curriculum/
Summer Supercomputing Academy. http://academy.hpc-russia.ru/
Supercomputing Education in Russia, Supercomputing Consortium of the Russian Universities. http://hpc.msu.ru/files/HPC-Education-in-Russia.pdf (2012)
Acknowledgements
This project is being conducted at Moscow State University with financial support from the Russian Science Foundation, Agreement No 14-11-00190.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Voevodin, V.V. (2016). Parallel Algorithms: Theory, Practice and Education. In: Resch, M., Bez, W., Focht, E., Patel, N., Kobayashi, H. (eds) Sustained Simulation Performance 2016. Springer, Cham. https://doi.org/10.1007/978-3-319-46735-1_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-46735-1_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-46734-4
Online ISBN: 978-3-319-46735-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)