The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
GPUs and the Future of Parallel Computing
Abstract
This article discusses the capabilities of state-of-the art GPU-based high-throughput computing systems and considers the challenges to scaling single-chip parallel-computing systems, highlighting high-impact areas that the computing research community can address. Nvidia Research is investigating an architecture for a heterogeneous high-performance computing system that seeks to address these challenges.
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Citations
Cites
Nickolls, J., & Dally, W. J. (2010) · IEEE Micro · doi:10.1109/mm.2010.41 · Cited by 980
Self-citationAutomatically Tuned Linear Algebra Software
Whaley, R. C., & Dongarra, J. J. (1998) · Conference on High Performance Computing (Supercomputing) · doi:10.5555/509058.509096 · Cited by 854
Automatically Tuned Linear Algebra Software
Whaley, R. C., & Dongarra, J. J. (1998) · Proceedings of the IEEE/ACM SC98 Conference · doi:10.1109/sc.1998.10004 · Cited by 527
Understanding the Energy Consumption of Dynamic Random Access Memories
Vogelsang, T. (2010) · 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture · doi:10.1109/micro.2010.42 · Cited by 257
Energy-Efficient Floating-Point Unit Design
Galal, S., & Horowitz, M. (2010) · IEEE Transactions on Computers · doi:10.1109/tc.2010.121 · Cited by 132
Cited by
Memory devices and applications for in-memory computing
Sebastian, A., Le Gallo, M., Khaddam-Aljameh, R., & Eleftheriou, E. (2020) · Nature Nanotechnology · doi:10.1038/s41565-020-0655-z · Cited by 2,289
A crossbar array of magnetoresistive memory devices for in-memory computing
Jung, S., Lee, H., Myung, S., Kim, H., Yoon, S. K., Kwon, S.-W., Ju, Y., Kim, M., Yi, W., Han, S., et al. (2022) · Nature · doi:10.1038/s41586-021-04196-6 · Cited by 644
Amirsoleimani, A., Alibart, F., Yon, V., Xu, J., Pazhouhandeh, M. R., Ecoffey, S., Beilliard, Y., Genov, R., & Drouin, D. (2020) · Advanced Intelligent Systems · doi:10.1002/aisy.202000115 · Cited by 216
Opportunities for Nonvolatile Memory Systems in Extreme-Scale High-Performance Computing
Vetter, J. S., & Mittal, S. (2015) · Computing in Science & Engineering · doi:10.1109/mcse.2015.4 · Cited by 95
Romanov, S., Siqueira, A. S., de Bruin, J., Teijema, J., Hofstee, L., & van de Schoot, R. (2024) · Data Intelligence · doi:10.1162/dint_a_00244 · Cited by 7
Metadata
- Authors
- Keckler, S. W., Dally, W. J., Khailany, B., Garland, M., & Glasco, D.
- Venue
- IEEE Micro
- Published
- 2011-09
- Volume
- 31
- Issue
- 5
- Pages
- 7-17
- ISSN
- 0272-1732 (ISSN-L)
- OpenAlex
- W2024122052
- Cited by
- 658
- References
- 5
- FWCI
- 60.54
- Type
- journal article
- Language
- en
- Open access
- closed
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- Keckler, S. W., Dally, W. J., Khailany, B., Garland, M., & Glasco, D. (2011). GPUs and the Future of Parallel Computing. IEEE Micro. https://doi.org/10.1109/mm.2011.89
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
