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- affiliation: Rutgers University
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2020 – today
- 2023
[j154]Zhe Wang, Matthieu Dorier, Pradeep Subedi, Philip E. Davis, Manish Parashar:
Adaptive elasticity policies for staging-based in situ visualization. Future Gener. Comput. Syst. 142: 75-89 (2023)- [j153]Manish Parashar
:
Editorial. IEEE Trans. Parallel Distributed Syst. 34(2): 429-430 (2023) - 2022
- [j152]Manish Parashar, Amy Friedlander, Erwin P. Gianchandani, Margaret Martonosi:
Transforming science through cyberinfrastructure. Commun. ACM 65(8): 30-32 (2022) - [j151]Manish Parashar:
Advancing Reproducibility in Parallel and Distributed Systems Research. Computer 55(5): 4-5 (2022) - [j150]Manish Parashar, Michael A. Heroux, Victoria Stodden:
Research Reproducibility. Computer 55(8): 16-18 (2022) - [j149]Manish Parashar:
Democratizing Science Through Advanced Cyberinfrastructure. Computer 55(9): 79-84 (2022) - [j148]Charlie Catlett, Pete Beckman, Nicola J. Ferrier, Michael E. Papka, Rajesh Sankaran, Jeff Solin, Valerie E. Taylor, Douglas Pancoast, Daniel A. Reed, Manish Parashar, David Abramson:
Hands-On Computer Science: The Array of Things Experimental Urban Instrument. Comput. Sci. Eng. 24(1): 57-63 (2022) - [j147]James M. Brase, Nancy Campbell, Barbara Helland, Thuc Hoang, Manish Parashar, Michael Rosenfield, James C. Sexton, John Towns, Kathryn Mohror, John M. Shalf:
The COVID-19 High-Performance Computing Consortium. Comput. Sci. Eng. 24(1): 78-85 (2022) - [j146]Yubo Qin, Ivan Rodero, Manish Parashar:
Toward Democratizing Access to Facilities Data: A Framework for Intelligent Data Discovery and Delivery. Comput. Sci. Eng. 24(3): 52-60 (2022) - [j145]Manish Parashar:
Jack Dongarra: Catalyzing the Transformation of High-Performance Computing. Comput. Sci. Eng. 24(4): 4-5 (2022) - [j144]Manish Parashar, David Abramson:
Accidental Translationists: A Perspective From the Trenches. Comput. Sci. Eng. 24(4): 70-75 (2022) - [j143]Eric Suchyta, Scott Klasky, Norbert Podhorszki, Matthew Wolf, Abolaji D. Adesoji, Choong-Seock Chang, Jong Choi, Philip E. Davis, Julien Dominski, Stéphane Ethier, Ian T. Foster, Kai Germaschewski, Berk Geveci, Chris Harris, Kevin A. Huck, Qing Liu, Jeremy Logan, Kshitij Mehta, Gabriele Merlo, Shirley V. Moore, Todd S. Munson, Manish Parashar, David Pugmire, Mark S. Shephard, Cameron W. Smith, Pradeep Subedi, Lipeng Wan, Ruonan Wang, Shuangxi Zhang:
The Exascale Framework for High Fidelity coupled Simulations (EFFIS): Enabling whole device modeling in fusion science. Int. J. High Perform. Comput. Appl. 36(1): 106-128 (2022) - [j142]Muhammad K. Ali, Ashiq Anjum, Omer F. Rana, Ali Reza Zamani, Daniel Balouek-Thomert, Manish Parashar:
RES: Real-Time Video Stream Analytics Using Edge Enhanced Clouds. IEEE Trans. Cloud Comput. 10(2): 792-804 (2022) - [j141]Manish Parashar:
EiC Editorial - Advancing Reproducibility in Parallel and Distributed Systems Research. IEEE Trans. Parallel Distributed Syst. 33(9): 2010 (2022) - [j140]Moustafa AbdelBaky, Manish Parashar:
A General Performance and QoS Model for Distributed Software-Defined Environments. IEEE Trans. Serv. Comput. 15(1): 228-240 (2022) - [c240]Bo Zhang, Pradeep Subedi, Philip E. Davis, Francesco Rizzi, Keita Teranishi, Manish Parashar:
Assembling Portable In-Situ Workflow from Heterogeneous Components using Data Reorganization. CCGRID 2022: 41-50 - [c239]Manish Parashar:
Data-Management for Extreme Science: Experiences in Translational Computer Science Research. HPDC 2022: 3 - [c238]Matthieu Dorier, Zhe Wang, Utkarsh Ayachit, Shane Snyder, Robert B. Ross, Manish Parashar:
Colza: Enabling Elastic In Situ Visualization for High-performance Computing Simulations. IPDPS 2022: 538-548 - [c237]Zhe Wang, Matthieu Dorier, Manish Parashar:
Research Perspectives Toward Autonomic Optimization of In Situ Analysis and Visualization. ISAV@SC 2022: 7-13 - [c236]Moustafa AbdelBaky, Manish Parashar:
A General Performance and QoS Model for Distributed Software-Defined Environments. SERVICES 2022: 28 - 2021
- [j139]Manish Parashar:
Enabling Reproducible Research in Parallel and Distributed Systems. Computer 54(7): 4-5 (2021) - [j138]Manish Parashar, David Abramson:
Translational Computer Science for Science and Engineering. Comput. Sci. Eng. 23(5): 5-6 (2021) - [j137]Yubo Qin, Ivan Rodero, Anthony Simonet, Charles Meertens, Daniel Reiner, James Riley, Manish Parashar:
Leveraging user access patterns and advanced cyberinfrastructure to accelerate data delivery from shared-use scientific observatories. Future Gener. Comput. Syst. 122: 14-27 (2021) - [j136]Ian T. Foster, Mark Ainsworth, Julie Bessac, Franck Cappello, Jong Choi, Sheng Di, Zichao Wendy Di, Ali Murat Gok, Hanqi Guo, Kevin A. Huck, Christopher Kelly, Scott Klasky, Kerstin Kleese van Dam, Xin Liang, Kshitij Mehta, Manish Parashar, Tom Peterka, Line Pouchard, Tong Shu, Ozan Tugluk, Hubertus Van Dam, Lipeng Wan, Matthew Wolf, Justin M. Wozniak, Wei Xu, Igor Yakushin, Shinjae Yoo, Todd S. Munson:
Online data analysis and reduction: An important Co-design motif for extreme-scale computers. Int. J. High Perform. Comput. Appl. 35(6): 617-635 (2021) - [j135]Ioan Petri, Omer F. Rana, Luiz F. Bittencourt, Daniel Balouek-Thomert, Manish Parashar:
Autonomics at the Edge: Resource Orchestration for Edge Native Applications. IEEE Internet Comput. 25(4): 21-29 (2021) - [j134]David Abramson, Manish Parashar, Peter W. Arzberger:
Translation computer science - Overview of the special issue. J. Comput. Sci. 52: 101227 (2021) - [j133]Manish Parashar:
Editor's Note. IEEE Trans. Parallel Distributed Syst. 32(4): 743-745 (2021) - [j132]Manish Parashar:
Editor's Note. IEEE Trans. Parallel Distributed Syst. 32(10): 2381-2385 (2021) - [j131]Manish Parashar:
Guest Editorial: Special Section on SC19 Student Cluster Competition. IEEE Trans. Parallel Distributed Syst. 32(11): 2606 (2021) - [c235]Pradeep Subedi, Philip E. Davis, Manish Parashar:
RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows. CLUSTER 2021: 146-156 - [c234]Zhe Wang, Pradeep Subedi, Matthieu Dorier, Philip E. Davis, Manish Parashar:
Adaptive Placement of Data Analysis Tasks For Staging Based In-Situ Processing. HiPC 2021: 242-251 - [c233]Daniel Balouek-Thomert, Manish Parashar:
Platforms for Edge Computing and Internet of Things applications: A survey. IC3 2021: 140-149 - [c232]Yubo Qin, Ivan Rodero, Manish Parashar:
Facilitating Data Discovery for Large-scale Science Facilities using Knowledge Networks. IPDPS 2021: 651-660 - [c231]Zhe Wang, Pradeep Subedi, Matthieu Dorier, Philip E. Davis, Manish Parashar:
Facilitating Staging-based Unstructured Mesh Processing to Support Hybrid In-Situ Workflows. IPDPS Workshops 2021: 960-964 - [c230]Zeina Houmani, Daniel Balouek-Thomert, Eddy Caron, Manish Parashar:
Enabling microservices management for Deep Learning applications across the Edge-Cloud Continuum. SBAC-PAD 2021: 137-146 - [c229]Daniel Balouek-Thomert, Ivan Rodero, Manish Parashar:
Evaluating policy-driven adaptation on the Edge-to-Cloud Continuum. UrgentHPC@SC 2021: 11-20 - [c228]Daniel Balouek-Thomert, Pedro Silva, Kevin Fauvel, Alexandru Costan, Gabriel Antoniu, Manish Parashar:
MDSC: modelling distributed stream processing across the edge-to-cloud continuum. UCC Companion 2021: 25:1-25:6 - [c227]Zhe Wang, Matthieu Dorier, Pradeep Subedi, Philip E. Davis, Manish Parashar:
An Adaptive Elasticity Policy For Staging Based In-Situ Processing. WORKS 2021: 33-41 - [i14]Azita Nouri, Philip E. Davis, Pradeep Subedi, Manish Parashar:
Scalable Graph Embedding LearningOn A Single GPU. CoRR abs/2110.06991 (2021) - [i13]Azita Nouri, Philip E. Davis, Pradeep Subedi, Manish Parashar:
Exploring the Role of Machine Learning in Scientific Workflows: Opportunities and Challenges. CoRR abs/2110.13999 (2021) - [i12]Yubo Qin, Ivan Rodero, Manish Parashar:
Toward Democratizing Access to Facilities Data: A Framework for Intelligent Data Discovery and Delivery. CoRR abs/2112.06479 (2021) - 2020
- [j130]Manish Parashar:
Parallel and Distributed Systems. Computer 53(11): 7-8 (2020) - [j129]Ali Reza Zamani, Moustafa AbdelBaky, Daniel Balouek-Thomert, Juan J. Villalobos, Ivan Rodero, Manish Parashar:
Submarine: A subscription-based data streaming framework for integrating large facilities and advanced cyberinfrastructure. Concurr. Comput. Pract. Exp. 32(16) (2020) - [j128]Manish Parashar, Anthony Simonet, Ivan Rodero, Forough Ghahramani, Grace Agnew, Ron Jantz, Vasant G. Honavar:
The Virtual Data Collaboratory: A Regional Cyberinfrastructure for Collaborative Data-Driven Research. Comput. Sci. Eng. 22(3): 79-92 (2020) - [j127]Ivan Rodero, Manish Parashar:
Data Cyberinfrastructure for End-to-End Science. Comput. Sci. Eng. 22(5): 60-71 (2020) - [j126]Ali Reza Zamani, Daniel Balouek-Thomert, Juan J. Villalobos, Ivan Rodero, Manish Parashar:
An edge-aware autonomic runtime for data streaming and in-transit processing. Future Gener. Comput. Syst. 110: 107-118 (2020) - [j125]Hank Childs, Sean Ahern, James P. Ahrens, Andrew C. Bauer, Janine Bennett, E. Wes Bethel, Peer-Timo Bremer, Eric Brugger, Joseph Cottam, Matthieu Dorier, Soumya Dutta, Jean M. Favre, Thomas Fogal, Steffen Frey, Christoph Garth, Berk Geveci, William F. Godoy, Charles D. Hansen, Cyrus Harrison, Bernd Hentschel, Joseph A. Insley, Christopher R. Johnson, Scott Klasky, Aaron Knoll, James Kress, Matthew Larsen, Jay F. Lofstead, Kwan-Liu Ma, Preeti Malakar, Jeremy S. Meredith, Kenneth Moreland, Paul A. Navrátil, Patrick O'Leary, Manish Parashar, Valerio Pascucci, John Patchett, Tom Peterka, Steve Petruzza, Norbert Podhorszki, David Pugmire, Michel E. Rasquin, Silvio Rizzi, David H. Rogers, Sudhanshu Sane, Franz Sauer, Robert Sisneros, Han-Wei Shen, Will Usher, Rhonda Vickery, Venkatram Vishwanath, Ingo Wald, Ruonan Wang, Gunther H. Weber, Brad Whitlock, Matthew Wolf, Hongfeng Yu, Sean B. Ziegeler:
A terminology for in situ visualization and analysis systems. Int. J. High Perform. Comput. Appl. 34(6) (2020) - [j124]Tong Jin, Fan Zhang, Qian Sun, Melissa Romanus, Hoang Bui, Manish Parashar:
Towards autonomic data management for staging-based coupled scientific workflows. J. Parallel Distributed Comput. 146: 35-51 (2020) - [j123]Daniel Balouek-Thomert, Ivan Rodero, Manish Parashar:
Harnessing the Computing Continuum for Urgent Science. SIGMETRICS Perform. Evaluation Rev. 48(2): 41-46 (2020) - [d1]William F. Godoy, Norbert Podhorszki, Ruonan Wang, Chuck Atkins, Greg Eisenhauer, Junmin Gu, Philip E. Davis, Jong Choi, Kai Germaschewski, Kevin A. Huck, Axel Huebl, Mark Kim, James Kress, Tahsin M. Kurç, Qing Liu, Jeremy Logan, Kshitij Mehta, George Ostrouchov, Manish Parashar, Franz Poeschel, David Pugmire, Eric Suchyta, Keichi Takahashi, Nick Thompson, Seiji Tsutsumi, Lipeng Wan, Matthew Wolf, Kesheng Wu, Scott Klasky:
ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management. SoftwareX 12: 100561 (2020) - [j122]Shiyan Hu, Xin Li, Haibo He, Shuguang Cui, Manish Parashar:
Big Data for Cyber-Physical Systems. IEEE Trans. Big Data 6(4): 606-608 (2020) - [j121]Ching-Hsien Hsu, Manish Parashar, Omer F. Rana:
Guest Editorial: Special Section on Advances of Utility and Cloud Computing Technologies and Services. IEEE Trans. Cloud Comput. 8(4): 972-974 (2020) - [j120]Shaohua Duan, Pradeep Subedi, Philip E. Davis, Keita Teranishi, Hemanth Kolla, Marc Gamell, Manish Parashar:
CoREC: Scalable and Resilient In-memory Data Staging for In-situ Workflows. ACM Trans. Parallel Comput. 7(2): 12:1-12:29 (2020) - [j119]Manish Parashar:
Editor's Note. IEEE Trans. Parallel Distributed Syst. 31(2): 251-252 (2020) - [j118]Ali Reza Zamani, Mengsong Zou, Javier Diaz Montes, Ioan Petri, Omer F. Rana, Ashiq Anjum, Manish Parashar:
Deadline Constrained Video Analysis via In-Transit Computational Environments. IEEE Trans. Serv. Comput. 13(1): 59-72 (2020) - [c226]Kevin Fauvel, Daniel Balouek-Thomert, Diego Melgar, Pedro Silva, Anthony Simonet, Gabriel Antoniu, Alexandru Costan, Véronique Masson, Manish Parashar, Ivan Rodero, Alexandre Termier:
A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning. AAAI 2020: 403-411 - [c225]Zeina Houmani, Daniel Balouek-Thomert, Eddy Caron, Manish Parashar:
Enhancing microservices architectures using data-driven service discovery and QoS guarantees. CCGRID 2020: 290-299 - [c224]Issam Raïs, Otto J. Anshus, John Markus Bjørndalen, Daniel Balouek-Thomert, Manish Parashar:
Trading Data Size and CNN Confidence Score for Energy Efficient CPS Node Communications. CCGRID 2020: 469-478 - [c223]Zhe Wang, Pradeep Subedi, Matthieu Dorier, Philip E. Davis, Manish Parashar:
Staging Based Task Execution for Data-driven, In-Situ Scientific Workflows. CLUSTER 2020: 209-220 - [c222]Shaohua Duan, Manish Parashar:
Scalable Crash Consistency for Staging-based In-situ Scientific Workflows. IPDPS Workshops 2020: 340-348 - [c221]Shaleen Garg, Sudarsun Kannan, Manish Parashar:
The Need for Precise and Efficient Memory Capacity Budgeting. MEMSYS 2020: 169-177 - [c220]Philip E. Davis, Pradeep Subedi, Shaohua Duan, Lee F. Ricketson, Jeffrey A. F. Hittinger, Manish Parashar:
Benesh: a Programming Model for Coupled Scientific Workflows. ESPM2@SC 2020: 1-9 - [e25]Manish Parashar, Vladimir Vlassov, David E. Irwin, Kathryn Mohror:
HPDC '20: The 29th International Symposium on High-Performance Parallel and Distributed Computing, Stockholm, Sweden, June 23-26, 2020. ACM 2020, ISBN 978-1-4503-7052-3 [contents] - [i11]Zhe Wang, Pradeep Subedi, Shaohua Duan, Yubo Qin, Philip E. Davis, Anthony Simonet, Ivan Rodero, Manish Parashar:
Exploring Trade-offs in Dynamic Task Triggering for Loosely Coupled Scientific Workflows. CoRR abs/2004.10381 (2020) - [i10]Yubo Qin, Ivan Rodero, Anthony Simonet, Charles Meertens, Daniel Reiner, James Riley, Manish Parashar:
Leveraging User Access Patterns and Advanced Cyberinfrastructure to Accelerate Data Delivery from Shared-use Scientific Observatories. CoRR abs/2012.15321 (2020)
2010 – 2019
- 2019
- [j117]David Abramson, Manish Parashar:
Translational Research in Computer Science. Computer 52(9): 16-23 (2019) - [j116]Manish Parashar:
The Reproducibility Initiative. Computer 52(11): 7-8 (2019) - [j115]Daniel Balouek-Thomert, Eduard Gibert Renart, Ali Reza Zamani, Anthony Simonet, Manish Parashar:
Towards a computing continuum: Enabling edge-to-cloud integration for data-driven workflows. Int. J. High Perform. Comput. Appl. 33(6) (2019) - [j114]Edward Chuah, Arshad Jhumka, Samantha Alt, Daniel Balouek-Thomert, James C. Browne, Manish Parashar:
Towards comprehensive dependability-driven resource use and message log-analysis for HPC systems diagnosis. J. Parallel Distributed Comput. 132: 95-112 (2019) - [j113]Manish Parashar:
Editor's Note. IEEE Trans. Parallel Distributed Syst. 30(1): 1 (2019) - [j112]Manish Parashar:
Editor's Note. IEEE Trans. Parallel Distributed Syst. 30(8): 1687-1689 (2019) - [j111]Manish Parashar:
Editor's Note: IEEE Transactions on Parallel and Distributed Systems (TPDS) Reproducibility Initiative, June 2019. IEEE Trans. Parallel Distributed Syst. 30(8): 1690 (2019) - [c219]Xuan Hu, Jie Gong, Eduard Gibert Renart, Manish Parashar:
Two-Stage Framework for Big Spatial Data Analytics to Support Disaster Response. IEEE BigData 2019: 5409-5418 - [c218]Shouwei Chen, Wensheng Wang, Xueyang Wu, Zhen Fan, Kunwu Huang, Peiyu Zhuang, Yue Li, Ivan Rodero, Manish Parashar, Dennis Z. Weng:
Optimizing Performance and Computing Resource Management of In-memory Big Data Analytics with Disaggregated Persistent Memory. CCGRID 2019: 21-30 - [c217]Eduard Gibert Renart, Alexandre Da Silva Veith, Daniel Balouek-Thomert, Marcos Dias de Assunção, Laurent Lefèvre, Manish Parashar:
Distributed Operator Placement for IoT Data Analytics Across Edge and Cloud Resources. CCGRID 2019: 459-468 - [c216]Pradeep Subedi, Philip E. Davis, Manish Parashar:
Leveraging Machine Learning for Anticipatory Data Delivery in Extreme Scale In-situ Workflows. CLUSTER 2019: 1-11 - [c215]Yubo Qin, Anthony Simonet, Philip E. Davis, Azita Nouri, Zhe Wang, Manish Parashar, Ivan Rodero:
Towards a Smart, Internet-Scale Cache Service for Data Intensive Scientific Applications. ScienceCloud@HPDC 2019: 11-18 - [c214]Issam Raïs, Daniel Balouek-Thomert, Anne-Cécile Orgerie, Laurent Lefèvre, Manish Parashar:
Leveraging energy-efficient non-lossy compression for data-intensive applications. HPCS 2019: 463-469 - [c213]Eduard Gibert Renart, Daniel Balouek-Thomert, Manish Parashar:
An Edge-Based Framework for Enabling Data-Driven Pipelines for IoT Systems. IPDPS Workshops 2019: 885-894 - [c212]Edward Chuah, Arshad Jhumka, Samantha Alt, Juan J. Villalobos, Joshua Fryman, William Barth, Manish Parashar:
Using Resource Use Data and System Logs for HPC System Error Propagation and Recovery Diagnosis. ISPA/BDCloud/SocialCom/SustainCom 2019: 458-467 - [c211]Shaohua Duan, Pradeep Subedi, Philip E. Davis, Manish Parashar:
Addressing data resiliency for staging based scientific workflows. SC 2019: 87:1-87:22 - [i9]Eduard Gibert Renart, Daniel Balouek-Thomert, Manish Parashar:
Challenges in designing edge-based middlewares for the Internet of Things: A survey. CoRR abs/1912.06567 (2019) - 2018
- [j110]Ali Reza Zamani, Mengsong Zou, Javier Diaz Montes, Ioan Petri, Omer F. Rana, Manish Parashar:
A computational model to support in-network data analysis in federated ecosystems. Future Gener. Comput. Syst. 80: 342-354 (2018) - [j109]Yunbo Li, Anne-Cécile Orgerie, Ivan Rodero, Betsegaw Lemma Amersho, Manish Parashar, Jean-Marc Menaud:
End-to-end energy models for Edge Cloud-based IoT platforms: Application to data stream analysis in IoT. Future Gener. Comput. Syst. 87: 667-678 (2018) - [j108]Moustafa AbdelBaky, Javier Diaz Montes, Manish Parashar:
Software-defined environments for science and engineering. Int. J. High Perform. Comput. Appl. 32(1): 104-122 (2018) - [j107]Ewa Deelman, Tom Peterka, Ilkay Altintas, Christopher D. Carothers, Kerstin Kleese van Dam, Kenneth Moreland, Manish Parashar, Lavanya Ramakrishnan, Michela Taufer, Jeffrey S. Vetter:
The future of scientific workflows. Int. J. High Perform. Comput. Appl. 32(1): 159-175 (2018) - [j106]Manish Parashar, Franco Zambonelli:
Farewell Editorial. ACM Trans. Auton. Adapt. Syst. 12(4): 17:1-17:2 (2018) - [j105]Javier Diaz Montes, Manuel Diaz-Granados, Mengsong Zou, Shu Tao, Manish Parashar:
Supporting Data-Intensive Workflows in Software-Defined Federated Multi-Clouds. IEEE Trans. Cloud Comput. 6(1): 250-263 (2018) - [j104]Manish Parashar:
State of the Journal. IEEE Trans. Parallel Distributed Syst. 29(1): 1 (2018) - [c210]Jong Youl Choi, Choong-Seock Chang, Julien Dominski, Scott Klasky, Gabriele Merlo, Eric Suchyta, Mark Ainsworth, Bryce Allen, Franck Cappello, Michael Churchill, Philip E. Davis, Sheng Di, Greg Eisenhauer, Stéphane Ethier, Ian T. Foster, Berk Geveci, Hanqi Guo, Kevin A. Huck, Frank Jenko, Mark Kim, James Kress, Seung-Hoe Ku, Qing Liu, Jeremy Logan, Allen D. Malony, Kshitij Mehta, Kenneth Moreland, Todd S. Munson, Manish Parashar, Tom Peterka, Norbert Podhorszki, Dave Pugmire, Ozan Tugluk, Ruonan Wang, Ben Whitney, Matthew Wolf, Chad Wood:
Coupling Exascale Multiphysics Applications: Methods and Lessons Learned. eScience 2018: 442-452 - [c209]Manish Parashar:
Data Management, In-Situ Workflows and Extreme Scales. ROSS@HPDC 2018: 1:1 - [c208]Scott Klasky, Matthew Wolf, Mark Ainsworth, Chuck Atkins, Jong Choi, Greg Eisenhauer, Berk Geveci, William F. Godoy, Mark Kim, James Kress, Tahsin M. Kurç, Qing Liu, Jeremy Logan, Arthur B. Maccabe, Kshitij Mehta, George Ostrouchov, Manish Parashar, Norbert Podhorszki, David Pugmire, Eric Suchyta, Lipeng Wan, Ruonan Wang:
A View from ORNL: Scientific Data Research Opportunities in the Big Data Age. ICDCS 2018: 1357-1368 - [c207]Muhammad K. Ali, Ashiq Anjum, Muhammad Usman Yaseen, Ali Reza Zamani, Daniel Balouek-Thomert, Omer F. Rana, Manish Parashar:
Edge Enhanced Deep Learning System for Large-Scale Video Stream Analytics. ICFEC 2018: 1-10 - [c206]Manish Parashar:
HCW 2018 Keynote Talk 1. IPDPS Workshops 2018: 5 - [c205]Shaohua Duan, Pradeep Subedi, Keita Teranishi, Philip E. Davis, Hemanth Kolla, Marc Gamell, Manish Parashar:
Scalable Data Resilience for In-memory Data Staging. IPDPS 2018: 105-115 - [c204]Shadi Ibrahim, Manish Parashar, Anna Queralt, Domenico Talia:
Introduction to CEBDA 2018. IPDPS Workshops 2018: 1204 - [c203]Yubo Qin, Ivan Rodero, Pradeep Subedi, Manish Parashar, Sandro Rigo:
Exploring Power Budget Scheduling Opportunities and Tradeoffs for AMR-Based Applications. SBAC-PAD 2018: 57-64 - [c202]Ali Reza Zamani, Daniel Balouek-Thomert, Juan J. Villalobos, Ivan Rodero, Manish Parashar:
Runtime Management of Data Quality for Scientific Observatories Using Edge and In-Transit Resources. SBAC-PAD 2018: 274-281 - [c201]Pradeep Subedi, Philip E. Davis, Shaohua Duan, Scott Klasky, Hemanth Kolla, Manish Parashar:
Stacker: an autonomic data movement engine for extreme-scale data staging-based in-situ workflows. SC 2018: 73:1-73:11 - [c200]Ioan Petri, Ali Reza Zamani, Daniel Balouek-Thomert, Omer F. Rana, Yacine Rezgui, Manish Parashar:
Ensemble-Based Network Edge Processing. UCC 2018: 133-142 - [i8]Pradeep Subedi, Philip E. Davis, Juan J. Villalobos, Ivan Rodero, Manish Parashar:
Using Intel Optane Devices for In-situ Data Staging in HPC Workflows. CoRR abs/1807.09651 (2018) - [i7]Eduard Gibert Renart, Daniel Balouek-Thomert, Manish Parashar:
Edge Based Data-Driven Pipelines (Technical Report). CoRR abs/1808.01353 (2018) - 2017
- [j103]Luiz F. Bittencourt, Javier Diaz Montes, Rajkumar Buyya, Omer F. Rana, Manish Parashar:
Mobility-Aware Application Scheduling in Fog Computing. IEEE Cloud Comput. 4(2): 26-35 (2017) - [j102]Rafael Tolosana-Calasanz, Javier Diaz Montes, Omer F. Rana, Manish Parashar, Erotokritos Xydas, Charalampos E. Marmaras, Panagiotis Papadopoulos, Liana Cipcigan:
Computational resource management for data-driven applications with deadline constraints. Concurr. Comput. Pract. Exp. 29(8) (2017) - [j101]Fan Zhang, Tong Jin, Qian Sun, Melissa Romanus, Hoang Bui, Scott Klasky, Manish Parashar:
In-memory staging and data-centric task placement for coupled scientific simulation workflows. Concurr. Comput. Pract. Exp. 29(12) (2017) - [j100]Marc Gamell, Keita Teranishi, Hemanth Kolla, Jackson R. Mayo, Michael A. Heroux, Jacqueline Chen, Manish Parashar:
Scalable Failure Masking for Stencil Computations using Ghost Region Expansion and Cell to Rank Remapping. SIAM J. Sci. Comput. 39(5) (2017) - [j99]Rafael Tolosana-Calasanz, Javier Diaz Montes, Omer F. Rana, Manish Parashar:
Feedback-Control & Queueing Theory-Based Resource Management for Streaming Applications. IEEE Trans. Parallel Distributed Syst. 28(4): 1061-1075 (2017) - [j98]