Jeff Rasley
Impact in
- Hardware and Architecture top 5%
- Parallel Computing and Optimization Techniques
- Computational Mathematics top 10%
Papers in
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- Topic Modeling 4
- Data Stream Mining Techniques 1
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- Software-Defined Networks and 5G 3
- Interconnection Networks and Systems 3
- Distributed and Parallel Computing Systems 2
- Co-authors
- Yuxiong He (8 shared papers)Olatunji Ruwase (7 shared papers)Samyam Rajbhandari (6 shared papers)Rodrigo Fonseca (5 shared papers)Kanak Agarwal (3 shared papers)John D. Carter (2 shared papers)Eric Rozner (3 shared papers)Brent Stephens (3 shared papers)
- Journals
- ACM SIGCOMM Computer Communication Review (1 paper)Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Jeff Rasley
15 papers receiving 1.3k citations
Jeff Rasley's Hit Papers
Peers
Comparison fields: 5 of 91
- Hardware and Architecture 186
- Computational Mathematics 15
- Artificial Intelligence 663
- Computer Networks and Communications 452
- Computer Vision and Pattern Recognition 378
Countries citing papers authored by Jeff Rasley
This map shows the geographic impact of Jeff Rasley's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jeff Rasley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeff Rasley more than expected).
Fields of papers citing papers by Jeff Rasley
This network shows the impact of papers produced by Jeff Rasley. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jeff Rasley. The network helps show where Jeff Rasley may publish in the future.
Co-authors
The 25 scholars most cited alongside Jeff Rasley, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | DeepSpeed Hit paper breakdown → | 2020 | 380 |
| 2 | ZeRO: Memory optimizations Toward Training Trillion Parameter Models Hit paper breakdown → | 2020 | 368 |
| 3 | 2021 | 131 | |
| 4 | 2014 | 116 | |
| 5 | 2022 | 108 | |
| 6 | 2014 | 64 | |
| 7 | 2016 | 64 | |
| 8 | 2010 | 28 | |
| 9 | ZeRO: Memory Optimization Towards Training A Trillion Parameter Models. | 2019 | 26 |
| 10 | 2017 | 22 | |
| 11 | 2015 | 13 | |
| 12 | 2023 | 4 | |
| 13 | Accelerating Large Scale Deep Learning Inference through DeepCPU at Microsoft. | 2019 | 3 |
| 14 | 2015 | 2 | |
| 15 | Low-latency Network Monitoring via Oversubscribed Port Mirroring | 2014 | 1 |
About Jeff Rasley
Jeff Rasley is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Hardware and Architecture and Electrical and Electronic Engineering, having authored 15 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (5 papers), Parallel Computing and Optimization Techniques (4 papers), Topic Modeling (4 papers), Advanced Optical Network Technologies (3 papers), Software-Defined Networks and 5G (3 papers), Interconnection Networks and Systems (3 papers), Distributed and Parallel Computing Systems (2 papers) and Data Stream Mining Techniques (1 paper). The work is most often cited by research in Hardware and Architecture (186 citations), Computational Mathematics (15 citations), Artificial Intelligence (663 citations), Computer Networks and Communications (452 citations) and Computer Vision and Pattern Recognition (378 citations). Jeff Rasley has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Yuxiong He, Olatunji Ruwase, Samyam Rajbhandari, Rodrigo Fonseca, Kanak Agarwal, John D. Carter, Eric Rozner, Brent Stephens, Colin Dixon and Wes Felter. Their work appears in journals such as ACM SIGCOMM Computer Communication Review and Proceedings of the AAAI Conference on Human Computation and Crowdsourcing.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.