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- Mallikarjun Shankar
aka: Mallikarjun Arjun Shankar
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Publication search results
found 56 matches
- 2023
- Junqi Yin, Feiyi Wang, Mallikarjun Arjun Shankar:
DeepThermo: Deep Learning Accelerated Parallel Monte Carlo Sampling for Thermodynamics Evaluation of High Entropy Alloys. IPDPS 2023: 333-343 - Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar:
FORGE: Pre-Training Open Foundation Models for Science. SC 2023: 81:1-81:13 - Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens:
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR abs/2310.04610 (2023) - Kuangdai Leng, Mallikarjun Shankar, Jeyan Thiyagalingam:
Zero Coordinate Shift: Whetted Automatic Differentiation for Physics-informed Operator Learning. CoRR abs/2311.00860 (2023) - 2022
- Junqi Yin, Feiyi Wang, Mallikarjun Shankar:
Strategies for Integrating Deep Learning Surrogate Models with HPC Simulation Applications. IPDPS Workshops 2022: 1-10 - Tainã Coleman, Henri Casanova, Ketan Maheshwari, Loïc Pottier, Sean R. Wilkinson, Justin M. Wozniak, Frédéric Suter, Mallikarjun Shankar, Rafael Ferreira da Silva:
WfBench: Automated Generation of Scientific Workflow Benchmarks. PMBS@SC 2022: 100-111 - Jeyan Thiyagalingam, Gregor von Laszewski, Junqi Yin, Murali Emani, Juri Papay, Gregg Barrett, Piotr Luszczek, Aristeidis Tsaris, Christine R. Kirkpatrick, Feiyi Wang, Tom Gibbs, Venkatram Vishwanath, Mallikarjun Shankar, Geoffrey C. Fox, Tony Hey:
AI Benchmarking for Science: Efforts from the MLCommons Science Working Group. ISC Workshops 2022: 47-64 - Tainã Coleman, Henri Casanova, Ketan Maheshwari, Loïc Pottier, Sean R. Wilkinson, Justin M. Wozniak, Frédéric Suter, Mallikarjun Shankar, Rafael Ferreira da Silva:
WfBench: Automated Generation of Scientific Workflow Benchmarks. CoRR abs/2210.03170 (2022) - 2021
- Katerina B. Antypas, Deborah Bard, Johannes P. Blaschke, Shane Richard Canon, Bjoern Enders, Mallikarjun Arjun Shankar, Suhas Somnath, Dale Stansberry, Thomas D. Uram, Sean R. Wilkinson:
Enabling discovery data science through cross-facility workflows. IEEE BigData 2021: 3671-3680 - Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin:
MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. MLHPC@SC 2021: 33-45 - Sajal Dash, Junqi Yin, Mallikarjun Shankar, Feiyi Wang, Wu-chun Feng:
Mitigating Catastrophic Forgetting in Deep Learning in a Streaming Setting Using Historical Summary. DRBSD@SC 2021: 11-18 - Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin:
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. CoRR abs/2110.11466 (2021) - Jeyan Thiyagalingam, Mallikarjun Shankar, Geoffrey C. Fox, Tony Hey:
Scientific Machine Learning Benchmarks. CoRR abs/2110.12773 (2021) - 2020
- George Ostrouchov, Don Maxwell, Rizwan A. Ashraf, Christian Engelmann, Mallikarjun Shankar, James H. Rogers:
GPU lifetimes on titan supercomputer: survival analysis and reliability. SC 2020: 41 - Dale Stansberry, Suhas Somnath, Gregory Shutt, Mallikarjun Shankar:
A Systemic Approach to Facilitating Reproducibility via Federated, End-to-End Data Management. SMC 2020: 83-98 - Dale Stansberry, Suhas Somnath, Jessica Breet, Gregory Shutt, Mallikarjun Shankar:
DataFed: Towards Reproducible Research via Federated Data Management. CoRR abs/2004.03710 (2020) - Shubhankar Gahlot, Junqi Yin, Mallikarjun Shankar:
Data optimization for large batch distributed training of deep neural networks. CoRR abs/2012.09272 (2020) - 2019
- David E. Womble, Mallikarjun Shankar, Wayne Joubert, J. Travis Johnston, Jack C. Wells, Jeffrey A. Nichols:
Early experiences on Summit: Data analytics and AI applications. IBM J. Res. Dev. 63(6): 2:1-2:9 (2019) - Junqi Yin, Shubhankar Gahlot, Nouamane Laanait, Ketan Maheshwari, Jack Morrison, Sajal Dash, Mallikarjun Shankar:
Strategies to Deploy and Scale Deep Learning on the Summit Supercomputer. DLS@SC 2019: 84-94 - 2018
- Sisi Duan, Sangkeun Lee, Supriya Chinthavali, Mallikarjun Shankar:
Best effort broadcast under cascading failures in interdependent critical infrastructure networks. Pervasive Mob. Comput. 43: 114-130 (2018) - Sudharshan S. Vazhkudai, Bronis R. de Supinski, Arthur S. Bland, Al Geist, James C. Sexton, Jim Kahle, Christopher Zimmer, Scott Atchley, Sarp Oral, Don E. Maxwell, Verónica G. Vergara Larrea, Adam Bertsch, Robin Goldstone, Wayne Joubert, Chris Chambreau, David Appelhans, Robert Blackmore, Ben Casses, George Chochia, Gene Davison, Matthew A. Ezell, Tom Gooding, Elsa Gonsiorowski, Leopold Grinberg, Bill Hanson, Bill Hartner, Ian Karlin, Matthew L. Leininger, Dustin Leverman, Chris Marroquin, Adam Moody, Martin Ohmacht, Ramesh Pankajakshan, Fernando Pizzano, James H. Rogers, Bryan S. Rosenburg, Drew Schmidt, Mallikarjun Shankar, Feiyi Wang, Py Watson, Bob Walkup, Lance D. Weems, Junqi Yin:
The design, deployment, and evaluation of the CORAL pre-exascale systems. SC 2018: 52:1-52:12 - Drew Schmidt, Junqi Yin, Michael A. Matheson, Bronson Messer, Mallikarjun Shankar:
Defining Big Data Analytics Benchmarks for Next Generation Supercomputers. CoRR abs/1811.02287 (2018) - 2017
- Sisi Duan, Sangkeun Lee, Supriya Chinthavali, Mallikarjun Shankar:
Best Effort Broadcast under Cascading Failures in Interdependent Networks. ICDCN 2017: 27 - 2016
- Byung H. Park, Özgür Özmen, Gil Weigand, Mallikarjun Shankar:
High-performance computing framework for predictive simulation of healthcare delivery innovation. BHI 2016: 517-520 - Sangkeun Lee, Liangzhe Chen, Sisi Duan, Supriya Chinthavali, Mallikarjun Shankar, B. Aditya Prakash:
URBAN-NET: A network-based infrastructure monitoring and analysis system for emergency management and public safety. IEEE BigData 2016: 2600-2609 - Eric J. Lingerfelt, Alex Belianinov, Eirik Endeve, O. Ovchinnikov, Suhas Somnath, Jose M. Borreguero, N. Grodowitz, B. Park, Richard K. Archibald, Christopher T. Symons, Sergei V. Kalinin, O. E. Bronson Messer, Mallikarjun Shankar, Stephen Jesse:
BEAM: A Computational Workflow System for Managing and Modeling Material Characterization Data in HPC Environments. ICCS 2016: 2276-2280 - Sangkeun Lee, Supriya Chinthavali, Sisi Duan, Mallikarjun Shankar:
Utilizing semantic big data for realizing a national-scale infrastructure vulnerability analysis system. SBD@SIGMOD 2016: 3 - 2015
- Rina Singh, Jeffrey A. Graves, Sangkeun Lee, Sreenivas R. Sukumar, Mallikarjun Shankar:
Enabling graph appliance for genome assembly. IEEE BigData 2015: 2583-2590 - Sangkeun Lee, Byung H. Park, Seung-Hwan Lim, Mallikarjun Shankar:
Table2Graph: A Scalable Graph Construction from Relational Tables Using Map-Reduce. BigDataService 2015: 294-301 - 2014
- Yubin Park, Mallikarjun Shankar, Byung-Hoon Park, Joydeep Ghosh:
Graph databases for large-scale healthcare systems: A framework for efficient data management and data services. ICDE Workshops 2014: 12-19
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