Jim Brandt

1.2k total citations
43 papers, 527 citations indexed

About

Jim Brandt is a scholar working on Computer Networks and Communications, Information Systems and Hardware and Architecture. According to data from OpenAlex, Jim Brandt has authored 43 papers receiving a total of 527 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Computer Networks and Communications, 20 papers in Information Systems and 14 papers in Hardware and Architecture. Recurrent topics in Jim Brandt's work include Distributed and Parallel Computing Systems (22 papers), Cloud Computing and Resource Management (17 papers) and Parallel Computing and Optimization Techniques (14 papers). Jim Brandt is often cited by papers focused on Distributed and Parallel Computing Systems (22 papers), Cloud Computing and Resource Management (17 papers) and Parallel Computing and Optimization Techniques (14 papers). Jim Brandt collaborates with scholars based in United States, Bulgaria and Mexico. Jim Brandt's co-authors include Ann Gentile, P.R. Norton, Philippe Pébaÿ, Benjamin A. Allan, Ann C. Gentile, Jeffrey A. Ogden, Mahesh Rajan, David Thompson, Nichamon Naksinehaboon and Michael Showerman and has published in prestigious journals such as IEEE Transactions on Parallel and Distributed Systems, Solid-State Electronics and IEEE Transactions on Nuclear Science.

In The Last Decade

Jim Brandt

40 papers receiving 508 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jim Brandt United States 12 407 251 130 88 74 43 527
Susan Coghlan United States 16 557 1.4× 348 1.4× 337 2.6× 90 1.0× 72 1.0× 27 661
Noah Treuhaft United States 6 504 1.2× 152 0.6× 231 1.8× 76 0.9× 149 2.0× 7 607
Guy A. Schiavone United States 7 212 0.5× 153 0.6× 132 1.0× 46 0.5× 21 0.3× 25 323
Steven W. Schlosser United States 13 728 1.8× 169 0.7× 390 3.0× 81 0.9× 96 1.3× 28 815
Xuechen Zhang United States 14 456 1.1× 157 0.6× 221 1.7× 54 0.6× 81 1.1× 51 587
Michael Showerman United States 6 300 0.7× 142 0.6× 206 1.6× 54 0.6× 38 0.5× 12 403
Jonathon Duerig United States 9 401 1.0× 153 0.6× 36 0.3× 98 1.1× 57 0.8× 15 461
Thanh Do Norway 10 462 1.1× 275 1.1× 62 0.5× 72 0.8× 73 1.0× 30 524
Don Maxwell United States 10 265 0.7× 93 0.4× 134 1.0× 170 1.9× 45 0.6× 17 374
D. Morató Spain 11 372 0.9× 174 0.7× 32 0.2× 120 1.4× 102 1.4× 69 497

Countries citing papers authored by Jim Brandt

Since Specialization
Citations

This map shows the geographic impact of Jim Brandt'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 Jim Brandt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jim Brandt more than expected).

Fields of papers citing papers by Jim Brandt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jim Brandt. 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 Jim Brandt. The network helps show where Jim Brandt may publish in the future.

Co-authorship network of co-authors of Jim Brandt

This figure shows the co-authorship network connecting the top 25 collaborators of Jim Brandt. A scholar is included among the top collaborators of Jim Brandt based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jim Brandt. Jim Brandt is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Schwaller, Benjamin, Vitus J. Leung, Jim Brandt, et al.. (2024). Runtime Performance Anomaly Diagnosis in Production HPC Systems Using Active Learning. IEEE Transactions on Parallel and Distributed Systems. 35(4). 693–706. 5 indexed citations
2.
Sato, Kento, Keiji Yamamoto, Fumiyoshi Shoji, et al.. (2024). Toward Sustainable HPC: In-Production Deployment of Incentive-Based Power Efficiency Mechanism on the Fugaku Supercomputer. 1–16. 6 indexed citations
3.
Schwaller, Benjamin, Vitus J. Leung, Jim Brandt, et al.. (2023). Prodigy: Towards Unsupervised Anomaly Detection in Production HPC Systems. 1–14. 4 indexed citations
4.
Goponenko, Alexander V., et al.. (2022). Metrics for Packing Efficiency and Fairness of HPC Cluster Batch Job Scheduling. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 241–252. 4 indexed citations
5.
Goponenko, Alexander V., et al.. (2021). Backfilling HPC Jobs with a Multimodal-Aware Predictor. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 618–622. 7 indexed citations
6.
Jha, Saurabh, Jim Brandt, Ann C. Gentile, et al.. (2020). Measuring Congestion in High-Performance Datacenter Interconnects. Networked Systems Design and Implementation. 37–57. 10 indexed citations
7.
Allan, Benjamin A., et al.. (2019). Production Application Performance Data Streaming for System Monitoring. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 4(2). 1–25. 2 indexed citations
8.
Zhang, Yijia, et al.. (2019). HPAS. 1–10. 7 indexed citations
9.
Zhang, Yijia, Ata Türk, Jim Brandt, et al.. (2018). Online Diagnosis of Performance Variation in HPC Systems Using Machine Learning. IEEE Transactions on Parallel and Distributed Systems. 30(4). 883–896. 42 indexed citations
10.
Naksinehaboon, Nichamon, et al.. (2018). Integrating Low-latency Analysis into HPC System Monitoring. Journal of International Crisis and Risk Communication Research. 1–10. 9 indexed citations
11.
Jha, Saurabh, Jim Brandt, Ann Gentile, et al.. (2017). Holistic Measurement-Driven System Assessment. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 797–800. 3 indexed citations
12.
Brandt, Jim, Karen Devine, & Ann Gentile. (2015). Infrastructure for In Situ System Monitoring and Application Data Analysis. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 36–40. 3 indexed citations
13.
Allan, Benjamin A., Jim Brandt, Ann Gentile, et al.. (2015). Toward Rapid Understanding of Production HPC Applications and Systems. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 464–473. 14 indexed citations
14.
Allan, Benjamin A., Jim Brandt, Jeremy Enos, et al.. (2014). The Lightweight Distributed Metric Service: A Scalable Infrastructure for Continuous Monitoring of Large Scale Computing Systems and Applications. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 154–165. 124 indexed citations
15.
Zheng, Ziming, et al.. (2012). Filtering log data: Finding the needles in the Haystack. 12 indexed citations
16.
Brandt, Jim, et al.. (2011). Baler: deterministic, lossless log message clustering tool. Computer Science - Research and Development. 26(3-4). 285–295. 21 indexed citations
17.
Brandt, Jim, et al.. (2010). SS Helium Vessel Development for 1.3 GHz SRF Cavities at Fermilab. 1 indexed citations
18.
Brandt, Jim, Ann Gentile, Jackson Mayo, et al.. (2009). Methodologies for advance warning of compute cluster problems via statistical analysis. 7–14. 9 indexed citations
19.
Brandt, Jim, et al.. (2008). Using Probabilistic Characterization to Reduce Runtime Faults in HPC Systems. 759–764. 7 indexed citations
20.
Brandt, Jim, et al.. (2006). OVIS: a tool for intelligent, real-time monitoring of computational clusters. International Parallel and Distributed Processing Symposium. 365–365. 13 indexed citations

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.

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