James Cipar
Impact in
- Information Systems top 5%
- Cloud Computing and Resource Management
- Hardware and Architecture top 5%
- Parallel Computing and Optimization Techniques
Papers in
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- Cloud Computing and Resource Management 4
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- Advanced Data Storage Technologies 3
- Advanced Database Systems and Queries 1
- Co-authors
- Gregory R. Ganger (10 shared papers)Seunghak Lee (3 shared papers)Garth A. Gibson (5 shared papers)Qirong Ho (3 shared papers)Michael A. Kozuch (5 shared papers)Henggang Cui (2 shared papers)Phillip B. Gibbons (2 shared papers)Eric P. Xing (2 shared papers)
- Journals
- ACM Transactions on Storage (3 papers)ScholarWorks@UMassAmherst (University of Massachusetts Amherst) (2 papers)Figshare (1 paper)KiltHub Repository (1 paper)Carolina Digital Repository (University of North Carolina at Chapel Hill) (1 paper)
- Partner nations
- United States
In The Last Decade
James Cipar
13 papers receiving 779 citations
James Cipar's Hit Papers
Peers
Comparison fields: 5 of 16
- Information Systems 209
- Hardware and Architecture 74
- Computer Networks and Communications 128
- Artificial Intelligence 164
- Computational Mathematics 1
Countries citing papers authored by James Cipar
This map shows the geographic impact of James Cipar'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 James Cipar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Cipar more than expected).
Fields of papers citing papers by James Cipar
This network shows the impact of papers produced by James Cipar. 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 James Cipar. The network helps show where James Cipar may publish in the future.
Co-authors
The 25 scholars most cited alongside James Cipar, 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 | More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server Hit paper breakdown → | 2013 | 367 |
| 2 | 2010 | 154 | |
| 3 | 2018 | 60 | |
| 4 | 2012 | 50 | |
| 5 | 2009 | 48 | |
| 6 | 2012 | 44 | |
| 7 | 2018 | 37 | |
| 8 | 2014 | 21 | |
| 9 | TFS: a transparent file system for contributory storage | 2007 | 12 |
| 10 | 2014 | 9 | |
| 11 | Transparent contribution of memory | 2006 | 8 |
| 12 | 2007 | 2 | |
| 13 | 2012 | 2 | |
| 14 | 2021 | 0 |
About James Cipar
James Cipar is a scholar working on Information Systems, Computer Networks and Communications, Cognitive Neuroscience, Artificial Intelligence and Nuclear Energy and Engineering, having authored 14 papers that have together received 814 indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (4 papers), Advanced Data Storage Technologies (3 papers), Memory Processes and Influences (1 paper), Advanced Database Systems and Queries (1 paper) and Stochastic Gradient Optimization Techniques (1 paper). The work is most often cited by research in Information Systems (209 citations), Hardware and Architecture (74 citations), Computer Networks and Communications (128 citations), Artificial Intelligence (164 citations) and Computational Mathematics (1 citation). James Cipar has collaborated with scholars based in United States. Frequent co-authors include Gregory R. Ganger, Seunghak Lee, Garth A. Gibson, Qirong Ho, Michael A. Kozuch, Henggang Cui, Phillip B. Gibbons, Eric P. Xing, Karsten Schwan and Varun Gupta. Their work appears in journals such as ACM Transactions on Storage, ScholarWorks@UMassAmherst (University of Massachusetts Amherst), Figshare, KiltHub Repository and Carolina Digital Repository (University of North Carolina at Chapel Hill).
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.