Grant Ayers
Impact in
- Hardware and Architecture top 2%
- Parallel Computing and Optimization Techniques
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- Advanced Data Storage Technologies
- Interconnection Networks and Systems
- Caching and Content Delivery
Papers in
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- Advanced Data Storage Technologies 6
- Interconnection Networks and Systems 3
- Distributed systems and fault tolerance 1
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- Parallel Computing and Optimization Techniques 8
- Co-authors
- Christos Kozyrakis (6 shared papers)Mingyu Gao (1 shared paper)Parthasarathy Ranganathan (6 shared papers)Heiner Litz (6 shared papers)Jung Ho Ahn (1 shared paper)Svilen Kanev (2 shared papers)Tipp Moseley (2 shared papers)David I. August (2 shared papers)
- Journals
- IEEE Micro (1 paper)International Conference on Machine Learning (1 paper)
- Partner nations
- United StatesUnited KingdomSouth Korea
In The Last Decade
Grant Ayers
8 papers receiving 410 citations
Peers
Comparison fields: 5 of 22
- Hardware and Architecture 310
- Computer Networks and Communications 299
- Information Systems 136
- Computer Vision and Pattern Recognition 59
- Electrical and Electronic Engineering 120
Countries citing papers authored by Grant Ayers
This map shows the geographic impact of Grant Ayers'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 Grant Ayers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Grant Ayers more than expected).
Fields of papers citing papers by Grant Ayers
This network shows the impact of papers produced by Grant Ayers. 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 Grant Ayers. The network helps show where Grant Ayers may publish in the future.
Co-authors
The 13 scholars most cited alongside Grant Ayers, 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 | 2015 | 198 | |
| 2 | 2018 | 54 | |
| 3 | 2020 | 52 | |
| 4 | 2019 | 48 | |
| 5 | 2022 | 23 | |
| 6 | 2022 | 21 | |
| 7 | 2020 | 18 | |
| 8 | Learning Memory Access Patterns | 2018 | 8 |
About Grant Ayers
Grant Ayers is a scholar working on Computer Networks and Communications, Hardware and Architecture, Information Systems, Electrical and Electronic Engineering and Infectious Diseases, having authored 8 papers that have together received 422 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (8 papers), Advanced Data Storage Technologies (6 papers), Cloud Computing and Resource Management (4 papers), Interconnection Networks and Systems (3 papers), Ferroelectric and Negative Capacitance Devices (1 paper), Distributed systems and fault tolerance (1 paper) and Advanced Memory and Neural Computing (1 paper). The work is most often cited by research in Hardware and Architecture (310 citations), Computer Networks and Communications (299 citations), Information Systems (136 citations), Computer Vision and Pattern Recognition (59 citations) and Electrical and Electronic Engineering (120 citations). Grant Ayers has collaborated with scholars based in United States, United Kingdom and South Korea. Frequent co-authors include Christos Kozyrakis, Mingyu Gao, Parthasarathy Ranganathan, Heiner Litz, Jung Ho Ahn, Svilen Kanev, Tipp Moseley, David I. August, Baris Kasikci and Milad Hashemi. Their work appears in journals such as IEEE Micro and International Conference on Machine Learning.
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.