Abstract
Communication costs, between processors and across the memory hierarchy, often dominate the runtime of algorithms. Can we trade these costs for recomputations? Most algorithms do not utilize recomputation for this end, and most communication cost lower bounds assume no recomputation, hence do not address this fundamental question. Recently, Bilardi and De Stefani (2017), and Bilardi, Scquizzato, and Silvestri (2018) showed that recomputations cannot reduce communication costs in Strassen's fast matrix multiplication and in fast Fourier transform. We extend the former bound and show that recomputations cannot reduce communication costs for a few other fast matrix multiplication algorithms.
| Original language | English |
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| Title of host publication | Proceedings - 2019 IEEE 33rd International Parallel and Distributed Processing Symposium, IPDPS 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 482-490 |
| Number of pages | 9 |
| ISBN (Electronic) | 9781728112466 |
| DOIs | |
| State | Published - May 2019 |
| Event | 33rd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2019 - Rio de Janeiro, Brazil Duration: 20 May 2019 → 24 May 2019 |
Publication series
| Name | Proceedings - 2019 IEEE 33rd International Parallel and Distributed Processing Symposium, IPDPS 2019 |
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Conference
| Conference | 33rd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2019 |
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| Country/Territory | Brazil |
| City | Rio de Janeiro |
| Period | 20/05/19 → 24/05/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE
Keywords
- Fast Matrix Multiplication
- I/O-complexity
- Memory Hierarchy
- Parallel Computation
- Recomputation