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2023 Journal Article Moving small files in a networked environmentJin, Chao, Abramson, David, Carroll, Jake, Liu, Zhengchun and Kettimuthu, Rajkumar (2023). Moving small files in a networked environment. Future Generation Computer Systems, 139, 167-180. doi: 10.1016/j.future.2022.09.016 |
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2022 Conference Publication Democratising large scale instrument-based science through e-InfrastructureAbramson, David, Barkauskas, Deborah S., Carroll, Jake, Condon, Nicholas D, Modhiran, Naphak, Nguyen, Hoang, Springfield, James, Watterson, Daniel and Jin, Chao (2022). Democratising large scale instrument-based science through e-Infrastructure. IEEE 18th International Conference on E-Science (E-Science), Salt Lake City, UT USA, 10-14 October 2022. New York, NY USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/escience55777.2022.00033 |
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2020 Conference Publication A BeeGFS-based caching file system for data-intensive parallel computingAbramson, David, Jin, Chao, Luong, Justin and Carroll, Jake (2020). A BeeGFS-based caching file system for data-intensive parallel computing. SCFA: Asian Conference on Supercomputing Frontiers, Singapore, Singapore, 24-27 February 2020. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-48842-0_1 |
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2019 Journal Article Statistical and machine learning models for optimizing energy in parallel applicationsEndrei, Mark, Jin, Chao, Dinh, Minh Ngoc, Abramson, David, Poxon, Heidi, DeRose, Luiz and de Supinski, Bronis R (2019). Statistical and machine learning models for optimizing energy in parallel applications. International Journal of High Performance Computing Applications, 33 (6), 109434201984291-1097. doi: 10.1177/1094342019842915 |
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2019 Book Chapter A Cache-based data movement infrastructure for on-demand scientific cloud computingAbramson, David, Carroll, Jake, Jin, Chao, Mallon, Michael, van Iperen, Zane, Nguyen, Hoang, McRae, Allan and Ming, Liang (2019). A Cache-based data movement infrastructure for on-demand scientific cloud computing. Supercomputing frontiers. (pp. 38-56) Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-18645-6_3 |
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2018 Journal Article A Bottleneck-Centric Tuning Policy for Optimizing Energy in Parallel ProgramsEndrei, Mark, Jin, Chao, Dinh, Minh, Abramson, David, Poxon, Heidi, DeRose, Luiz and De Supinski, Bronis R. (2018). A Bottleneck-Centric Tuning Policy for Optimizing Energy in Parallel Programs. Advances in Parallel Computing, 32, 265-276. doi: 10.3233/978-1-61499-843-3-265 |
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2018 Conference Publication Energy efficiency modeling of parallel applicationsEndrei, Mark, Jin, Chao, Dinh, Minh Ngoc, Abramson, David, Poxon, Heidi, DeRose, Luiz and de Supinski, Bronis R. (2018). Energy efficiency modeling of parallel applications. SC18: International Conference for High Performance Computing, Networking, Storage, and Analysis, Dallas, Texas, United States, 11-16 November 2018. Piscataway, NJ, United States: IEEE. doi: 10.1109/SC.2018.00020 |
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2017 Conference Publication A metropolitan area infrastructure for data intensive scienceAbramson, David, Carroll, Jake, Jin, Chao and Mallon, Michael (2017). A metropolitan area infrastructure for data intensive science. Annual IEEE International Conference on e-Science (e-Science), Auckland, New Zealand, 24-27 October 2017. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/eScience.2017.37 |
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2016 Journal Article A survey on software methods to improve the energy efficiency of parallel computingJin, Chao, de Supinski, Bronis R., Abramson, David, Poxon, Heidi, DeRose, Luiz, Dinh, Minh Ngoc, Endrei, Mark and Jessup, Elizabeth R. (2016). A survey on software methods to improve the energy efficiency of parallel computing. International Journal of High Performance Computing Applications, 31 (6), 517-549. doi: 10.1177/1094342016665471 |
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2016 Conference Publication Runtime verification of scientific codes using statisticsDinh, Minh Ngoc, Abramson, David and Jin, Chao (2016). Runtime verification of scientific codes using statistics. International Conference on Computational Science, ICCS 2016, San Diego, CA, United States, 6 - 8 June 2016. Amsterdam, Netherlands: Elsevier BV. doi: 10.1016/j.procs.2016.05.468 |
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2016 Conference Publication Runtime verification of scientific computing: towards an extreme scaleMinh Ngoc Dinh, Jin, Chao, Abramson, David and Jeffery, Clinton L. (2016). Runtime verification of scientific computing: towards an extreme scale. Workshop on Extreme-Scale Programming Tools (ESPT), Salt Lake City, UT, United States, 13-18 November 2016. Piscataway, NJ, United States: IEEE. doi: 10.1109/ESPT.2016.008 |
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2015 Journal Article A data-centric framework for debugging highly parallel applicationsDinh, Minh Ngoc, Abramson, David, Jin, Chao, Gontarek, Andrew, Moench, Bob and DeRose, Luiz (2015). A data-centric framework for debugging highly parallel applications. Software: Practice and Experience, 45 (4), 501-526. doi: 10.1002/spe.2239 |
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2015 Conference Publication Relative debugging for a highly parallel hybrid computer systemDeRose, Luiz, Gontarek, Andrew, Vose, Aaron, Moench, Robert, Abramson, David, Dinh, Minh Ngoc and Jin, Chao (2015). Relative debugging for a highly parallel hybrid computer system. International Conference for High Performance Computing, Networking, Storage and Analysis, Austin, TX, United States, 15-20 November 2015. New York, NY, United States: ACM. doi: 10.1145/2807591.2807605 |
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2014 Journal Article Statistical assertion: a more powerful method for debugging scientific applicationsDinh, Minh Ngoc, Abramson, David and Jin, Chao (2014). Statistical assertion: a more powerful method for debugging scientific applications. Journal of Computational Science, 5 (2), 126-134. doi: 10.1016/j.jocs.2013.12.002 |
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2014 Journal Article Scalable relative debuggingDinh, Minh Ngoc, Abramson, David and Jin, Chao (2014). Scalable relative debugging. IEEE Transactions on Parallel and Distributed Systems, 25 (3) 6487495, 740-749. doi: 10.1109/TPDS.2013.86 |
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2014 Conference Publication Supporting relative debugging for large-scale UPC programsDinh, Minh Ngoc, Abramson, David, Chao, Jin, Derose, Luiz, Moench, Bob and Gontarek, Andrew (2014). Supporting relative debugging for large-scale UPC programs. 14th Annual International Conference on Computational Science, ICCS 2014, Cairns, QLD Australia, 10-12 June 2014. Amsterdam, The Netherlands: Elsevier. doi: 10.1016/j.procs.2014.05.135 |
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2013 Conference Publication Extending the eclipse parallel tools platform debugger with scalable parallel debugging libraryJin, Chao, Ding, Liang and Abramson, David (2013). Extending the eclipse parallel tools platform debugger with scalable parallel debugging library. 13th Annual International Conference on Computational Science (ICCS), Barcelona, Spain, 5-7 June 2013. Amsterdam, The Netherlands: Elsevier. doi: 10.1016/j.procs.2013.05.346 |
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2012 Journal Article Scalable parallel debugging with statistical assertionsMinh Ngoc Dinh, Abramson, David, Jin, Chao, Gontarek, Andrew, Moench, Bob and DeRose, Luiz (2012). Scalable parallel debugging with statistical assertions. ACM SIGPLAN Notices, 47 (8), 311-312. doi: 10.1145/2370036.2145870 |
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2012 Conference Publication Scalable parallel debugging with statistical assertionsDinh, Minh Ngoc, Abramson, David, Jin, Chao, Gontarek, Andrew, Moench, Bob and DeRose, Luiz (2012). Scalable parallel debugging with statistical assertions. 17th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP'12, New Orleans, LA United States, 25 - 29 February 2012. New York, NY, USA: Association for Computing Machinery. doi: 10.1145/2145816.2145870 |
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2012 Conference Publication A scalable parallel debugging library with pluggable communication protocolsJin, Chao, Abramson, David, Dinh, Minh Ngo, Gontarek, Andrew, Moench, Robert and DeRose, Luiz (2012). A scalable parallel debugging library with pluggable communication protocols. 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2012, Ottawa, ON, 13 - 16 May 2012. Los Alamitos, Calif: I E E E Communications Society. doi: 10.1109/CCGrid.2012.13 |
