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Jim M. Brandt
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- affiliation: Sandia National Laboratories
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2020 – today
- 2024
- [j5]Burak Aksar
, Efe Sencan
Runtime Performance Anomaly Diagnosis in Production HPC Systems Using Active Learning. IEEE Trans. Parallel Distributed Syst. 35(4): 693-706 (2024) - [c44]Alexander V. Goponenko
Job Scheduling for HPC Clusters: Constraint Programming vs. Backfilling Approaches. DEBS 2024: 135-146 - [i5]Francieli Boito, Jim M. Brandt, Valeria Cardellini
Autonomy Loops for Monitoring, Operational Data Analytics, Feedback, and Response in HPC Operations. CoRR abs/2401.16971 (2024) - 2023
- [c43]Francieli Boito, Jim M. Brandt, Valeria Cardellini
Autonomy Loops for Monitoring, Operational Data Analytics, Feedback, and Response in HPC Operations. CLUSTER Workshops 2023: 37-43 - [c42]Kenneth Lamar
Evaluating HPC Job Run Time Predictions Using Application Input Parameters. DEBS 2023: 127-138 - [c41]Burak Aksar
Prodigy: Towards Unsupervised Anomaly Detection in Production HPC Systems. SC 2023: 26:1-26:14 - [i4]Jim M. Brandt, Florina M. Ciorba, Ann C. Gentile, Michael Ott, Torsten Wilde:
Driving HPC Operations With Holistic Monitoring and Operational Data Analytics (Dagstuhl Seminar 23171). Dagstuhl Reports 13(4): 98-120 (2023) - 2022
- [c40]Burak Aksar, Efe Sencan, Benjamin Schwaller, Omar Aaziz, Vitus J. Leung, Jim M. Brandt, Brian Kulis, Ayse K. Coskun
ALBADross: Active Learning Based Anomaly Diagnosis for Production HPC Systems. CLUSTER 2022: 369-380 - [c39]Alexander V. Goponenko, Kenneth Lamar, Christina L. Peterson, Benjamin A. Allan, Jim M. Brandt, Damian Dechev:
Metrics for Packing Efficiency and Fairness of HPC Cluster Batch Job Scheduling. SBAC-PAD 2022: 241-252 - 2021
- [c38]Kenneth Lamar, Alexander V. Goponenko, Christina L. Peterson, Benjamin A. Allan, Jim M. Brandt, Damian Dechev:
Backfilling HPC Jobs with a Multimodal-Aware Predictor. CLUSTER 2021: 618-622 - [c37]Burak Aksar
E2EWatch: An End-to-End Anomaly Diagnosis Framework for Production HPC Systems. Euro-Par 2021: 70-85 - [c36]Yijia Zhang, Burak Aksar
Using Monitoring Data to Improve HPC Performance via Network-Data-Driven Allocation. HPEC 2021: 1-7 - [c35]Archit Patke, Saurabh Jha, Haoran Qiu
Delay sensitivity-driven congestion mitigation for HPC systems. ICS 2021: 342-353 - [c34]Emily Costa, Tirthak Patel
Systematically inferring I/O performance variability by examining repetitive job behavior. SC 2021: 33 - [c33]Burak Aksar
Proctor: A Semi-Supervised Performance Anomaly Diagnosis Framework for Production HPC Systems. ISC 2021: 195-214 - 2020
- [c32]Benjamin Schwaller, Nick Tucker, Tom Tucker, Benjamin A. Allan, Jim M. Brandt:
HPC System Data Pipeline to Enable Meaningful Insights through Analysis-Driven Visualizations. CLUSTER 2020: 433-441 - [c31]Alexander V. Goponenko, Ramin Izadpanah, Jim M. Brandt, Damian Dechev:
Towards workload-adaptive scheduling for HPC clusters. CLUSTER 2020: 449-453 - [c30]Saurabh Jha
Measuring Congestion in High-Performance Datacenter Interconnects. NSDI 2020: 37-57 - [c29]Ron Brightwell, Kurt B. Ferreira, Ryan E. Grant, Scott Levy, Jay F. Lofstead
ALAMO: Autonomous Lightweight Allocation, Management, and Optimization. SMC 2020: 408-422 - [i3]Archit Patke, Saurabh Jha, Haoran Qiu, Jim M. Brandt, Ann C. Gentile, Joe Greenseid, Zbigniew Kalbarczyk, Ravishankar K. Iyer:
Application-aware Congestion Mitigation forHigh-Performance Computing Systems. CoRR abs/2012.07755 (2020)
2010 – 2019
- 2019
- [j4]Ramin Izadpanah
Production Application Performance Data Streaming for System Monitoring. ACM Trans. Model. Perform. Evaluation Comput. Syst. 4(2): 8:1-8:25 (2019) - [j3]Ozan Tuncer
Online Diagnosis of Performance Variation in HPC Systems Using Machine Learning. IEEE Trans. Parallel Distributed Syst. 30(4): 883-896 (2019) - [c28]Saurabh Jha
A Study of Network Congestion in Two Supercomputing High-Speed Interconnects. Hot Interconnects 2019: 45-48 - [c27]Emre Ates
HPAS: An HPC Performance Anomaly Suite for Reproducing Performance Variations. ICPP 2019: 40:1-40:10 - [i2]Valerio Formicola, Saurabh Jha, Daniel Chen, Fei Deng, Amanda Bonnie, Mike Mason, Jim M. Brandt, Ann C. Gentile, Larry Kaplan, Jason Repik, Jeremy Enos
Understanding Fault Scenarios and Impacts through Fault Injection Experiments in Cielo. CoRR abs/1907.01019 (2019) - [i1]Saurabh Jha, Archit Patke, Jim M. Brandt, Ann C. Gentile, Mike Showerman, Eric Roman, Zbigniew T. Kalbarczyk, William T. Kramer, Ravishankar K. Iyer:
A Study of Network Congestion in Two Supercomputing High-Speed Interconnects. CoRR abs/1907.05312 (2019) - 2018
- [c26]Ville Ahlgren, Stefan Andersson, Jim M. Brandt, Nicholas Cardo, Sudheer Chunduri
Large-Scale System Monitoring Experiences and Recommendations. CLUSTER 2018: 532-542 - [c25]Saurabh Jha
Characterizing Supercomputer Traffic Networks Through Link-Level Analysis. CLUSTER 2018: 562-570 - [c24]Emre Ates
Taxonomist: Application Detection Through Rich Monitoring Data. Euro-Par 2018: 92-105 - [c23]Ramin Izadpanah, Nichamon Naksinehaboon, Jim M. Brandt, Ann C. Gentile, Damian Dechev:
Integrating Low-latency Analysis into HPC System Monitoring. ICPP 2018: 5:1-5:10 - [c22]Kenneth Lamar, Ramin Izadpanah, Jim M. Brandt, Damian Dechev:
An Efficient Latch-free Database Index Based on Multi-dimensional Lists. IPCCC 2018: 1-2 - 2017
- [c21]Saurabh Jha
Holistic Measurement-Driven System Assessment. CLUSTER 2017: 797-800 - [c20]Ozan Tuncer, Emre Ates, Yijia Zhang, Ata Turk, Jim M. Brandt, Vitus J. Leung, Manuel Egele, Ayse K. Coskun:
Diagnosing Performance Variations in HPC Applications Using Machine Learning. ISC 2017: 355-373 - 2016
- [j2]Anthony M. Agelastos, Benjamin A. Allan, Jim M. Brandt, Ann C. Gentile, Sophia Lefantzi, Steve Monk, Jeff Ogden, Mahesh Rajan, Joel Stevenson:
Continuous whole-system monitoring toward rapid understanding of production HPC applications and systems. Parallel Comput. 58: 90-106 (2016) - [c19]Benjamin A. Allan, Jim M. Brandt, Ann C. Gentile, Cory Lueninghoener, Nichamon Naksinehaboon, Boyana Norris, Narate Taerat:
HPCMASPA Introduction and Committees. IPDPS Workshops 2016: 1665-1666 - [c18]Jim M. Brandt, Ann C. Gentile, Michael T. Showerman, Jeremy Enos
Large-Scale Persistent Numerical Data Source Monitoring System Experiences. IPDPS Workshops 2016: 1711-1720 - [c17]Sam Sanchez, Amanda Bonnie, Graham van Heule, Conor Robinson, Adam DeConinck, Kathleen Kelly, Quellyn Snead, Jim M. Brandt:
Design and Implementation of a Scalable HPC Monitoring System. IPDPS Workshops 2016: 1721-1725 - 2015
- [c16]Anthony M. Agelastos, Benjamin A. Allan, Jim M. Brandt, Ann C. Gentile, Sophia Lefantzi, Steve Monk, Jeff Ogden, Mahesh Rajan, Joel Stevenson:
Toward Rapid Understanding of Production HPC Applications and Systems. CLUSTER 2015: 464-473 - [c15]Jim M. Brandt, Ann C. Gentile, Cindy Martin, Jason Repik, Narate Taerat:
New Systems, New Behaviors, New Patterns: Monitoring Insights from System Standup. CLUSTER 2015: 658-665 - [c14]Steven D. Feldman, Deli Zhang, Damian Dechev, James Brandt:
Extending LDMS to Enable Performance Monitoring in Multi-core Applications. CLUSTER 2015: 717-720 - [c13]Jim M. Brandt, Karen D. Devine, Ann C. Gentile:
Infrastructure for In Situ System Monitoring and Application Data Analysis. ISAV@SC 2015: 36-40 - 2014
- [c12]Jim M. Brandt, Karen D. Devine, Ann C. Gentile, Kevin T. Pedretti:
Demonstrating improved application performance using dynamic monitoring and task mapping. CLUSTER 2014: 408-415 - [c11]Anthony M. Agelastos, Benjamin A. Allan, Jim M. Brandt, Paul Cassella, Jeremy Enos
The Lightweight Distributed Metric Service: A Scalable Infrastructure for Continuous Monitoring of Large Scale Computing Systems and Applications. SC 2014: 154-165 - 2012
- [c10]Li Yu, Ziming Zheng, Zhiling Lan, Terry R. Jones
Filtering log data: Finding the needles in the Haystack. DSN 2012: 1-12 - 2011
- [j1]Narate Taerat, Jim M. Brandt, Ann C. Gentile, Matthew Wong, Chokchai Leangsuksun:
Baler: deterministic, lossless log message clustering tool. Comput. Sci. Res. Dev. 26(3-4): 285-295 (2011) - [c9]Jim M. Brandt, Frank Chen, Ann C. Gentile, Chokchai Leangsuksun, Jackson R. Mayo, Philippe P. Pébay
Framework for Enabling System Understanding. Euro-Par Workshops (2) 2011: 231-240 - 2010
- [c8]James Brandt, Frank Chen, Vincent De Sapio, Ann C. Gentile, Jackson R. Mayo, Philippe P. Pébay
Using Cloud Constructs and Predictive Analysis to Enable Pre-Failure Process Migration in HPC Systems. CCGRID 2010: 703-708 - [c7]James Brandt, Frank Chen, Vincent De Sapio, Ann C. Gentile, Jackson R. Mayo, Philippe P. Pébay
Quantifying effectiveness of failure prediction and response in HPC systems: Methodology and example. DSN Workshops 2010: 2-7 - [c6]James Brandt, Frank Chen, Vincent De Sapio, Ann C. Gentile, Jackson R. Mayo, Philippe P. Pébay
Combining Virtualization, resource characterization, and Resource management to enable efficient high performance compute platforms through intelligent dynamic resource allocation. IPDPS Workshops 2010: 1-8
2000 – 2009
- 2009
- [c5]Jim M. Brandt, Ann C. Gentile, Jackson R. Mayo, Philippe P. Pébay
Resource monitoring and management with OVIS to enable HPC in cloud computing environments. IPDPS 2009: 1-8 - 2008
- [c4]Jim M. Brandt, Bert J. Debusschere
Using Probabilistic Characterization to Reduce Runtime Faults in HPC Systems. CCGRID 2008: 759-764 - [c3]Jim M. Brandt, Bert J. Debusschere, Ann C. Gentile, Jackson R. Mayo, Philippe P. Pébay
Ovis-2: A robust distributed architecture for scalable RAS. IPDPS 2008: 1-8 - 2006
- [c2]Jim M. Brandt, Ann C. Gentile, D. J. Hale, Philippe P. Pébay
OVIS: a tool for intelligent, real-time monitoring of computational clusters. IPDPS 2006 - 2005
- [c1]Jim M. Brandt, Ann C. Gentile, Youssef M. Marzouk, Philippe P. Pébay
Meaningful Automated Statistical Analysis of Large Computational Clusters. CLUSTER 2005: 1-2
Coauthor Index
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