Google
Google Scholar
Semantic Scholar
MS Academic
CiteSeerX
ORCIDManish Parashar
Person information
- affiliation: Rutgers University
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2021
[j129]Manish Parashar:
Editor's Note. IEEE Trans. Parallel Distributed Syst. 32(4): 743-745 (2021)- 2020
- [j128]Manish Parashar
:
Parallel and Distributed Systems. Computer 53(11): 7-8 (2020) - [j127]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) - [j126]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) - [j125]Ivan Rodero, Manish Parashar:
Data Cyberinfrastructure for End-to-End Science. Comput. Sci. Eng. 22(5): 60-71 (2020) - [j124]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) - [j123]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) - [j122]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) - [j121]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) - [j120]Ching-Hsien Hsu, Manish Parashar, Omer Rana:
Guest Editorial: Special Section on Advances of Utility and Cloud Computing Technologies and Services. IEEE Trans. Cloud Comput. 8(4): 972-974 (2020) - [j119]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) - [j118]Manish Parashar:
Editor's Note. IEEE Trans. Parallel Distributed Syst. 31(2): 251-252 (2020) - [j117]Ali Reza Zamani, Mengsong Zou, Javier Diaz Montes, Ioan Petri, Omer 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 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
- [j116]David Abramson, Manish Parashar:
Translational Research in Computer Science. Computer 52(9): 16-23 (2019) - [j115]Manish Parashar:
The Reproducibility Initiative. Computer 52(11): 7-8 (2019) - [j114]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) - [j113]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) - [j112]Manish Parashar:
Editor's Note. IEEE Trans. Parallel Distributed Syst. 30(1): 1 (2019) - [j111]Manish Parashar:
Editor's Note. IEEE Trans. Parallel Distributed Syst. 30(8): 1687-1689 (2019) - [j110]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
- [j109]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) - [j108]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) - [j107]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) - [j106]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) - [j105]Manish Parashar, Franco Zambonelli:
Farewell Editorial. ACM Trans. Auton. Adapt. Syst. 12(4): 17:1-17:2 (2018) - [j104]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) - [j103]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 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 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 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
- [j102]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) - [j101]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) - [j100]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) - [j99]Marc Gamell, Keita Teranishi, Hemanth Kolla, Jackson 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) - [j98]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) - [j97]Marc Gamell, Keita Teranishi, Jackson Mayo, Hemanth Kolla, Michael A. Heroux, Jacqueline Chen, Manish Parashar:
Modeling and Simulating Multiple Failure Masking Enabled by Local Recovery for Stencil-Based Applications at Extreme Scales. IEEE Trans. Parallel Distributed Syst. 28(10): 2881-2895 (2017) - [j96]Ioan Petri, Javier Diaz Montes, Omer F. Rana, Magdalena Punceva, Ivan Rodero, Manish Parashar:
Modelling and Implementing Social Community Clouds. IEEE Trans. Serv. Comput. 10(3): 410-422 (2017) - [c199]Juan J. Villalobos, Ivan Rodero, Manish Parashar:
An Unsupervised Approach for Online Detection and Mitigation of High-Rate DDoS Attacks Based on an In-Memory Distributed Graph Using Streaming Data and Analytics. BDCAT 2017: 103-112 - [c198]Yunbo Li, Anne-Cécile Orgerie, Ivan Rodero, Manish Parashar, Jean-Marc Menaud:
Leveraging Renewable Energy in Edge Clouds for Data Stream Analysis in IoT. CCGrid 2017: 186-195 - [c197]Moustafa AbdelBaky, Javier Diaz Montes, Merve Unuvar, Melissa Romanus, Ivan Rodero, Malgorzata Steinder, Manish Parashar:
Enabling Distributed Software-Defined Environments Using Dynamic Infrastructure Service Composition. CCGrid 2017: 274-283 - [c196]Moustafa AbdelBaky, Javier Diaz Montes, Manish Parashar:
Towards Distributed Software-Defined Environments. CCGrid 2017: 703-706 - [c195]Jong Youl Choi, Jeremy Logan, Matthew Wolf, George Ostrouchov, Tahsin M. Kurç, Qing Liu, Norbert Podhorszki, Scott Klasky, Melissa Romanus, Qian Sun, Manish Parashar, Randy Michael Churchill, Choong-Seock Chang:
TGE: Machine Learning Based Task Graph Embedding for Large-Scale Topology Mapping. CLUSTER 2017: 587-591 - [c194]Eduard Gibert Renart, Daniel Balouek-Thomert, Xuan Hu, Jie Gong, Manish Parashar:
Online Decision-Making Using Edge Resources for Content-Driven Stream Processing. eScience 2017: 384-392 - [c193]Ali Reza Zamani, Moustafa AbdelBaky, Daniel Balouek-Thomert, Ivan Rodero, Manish Parashar:
Supporting Data-Driven Workflows Enabled by Large Scale Observatories. eScience 2017: 592-595 - [c192]Ian T. Foster, Mark Ainsworth, Bryce Allen, Julie Bessac, Franck Cappello, Jong Youl Choi, Emil M. Constantinescu, Philip E. Davis, Sheng Di, Zichao Wendy Di, Hanqi Guo, Scott Klasky, Kerstin Kleese van Dam, Tahsin M. Kurç, Qing Liu, Abid Malik, Kshitij Mehta, Klaus Mueller, Todd Munson, George Ostrouchov, Manish Parashar, Tom Peterka, Line Pouchard, Dingwen Tao, Ozan Tugluk, Stefan M. Wild, Matthew Wolf, Justin M. Wozniak, Wei Xu, Shinjae Yoo:
Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales. Euro-Par 2017: 3-19 - [c191]Ali Reza Zamani, Ioan Petri, Javier Diaz Montes, Omer F. Rana, Manish Parashar:
Edge-Supported Approximate Analysis for Long Running Computations. FiCloud 2017: 321-328 - [c190]Moustafa AbdelBaky, Mengsong Zou, Ali Reza Zamani, Eduard Gibert Renart, Javier Diaz Montes, Manish Parashar:
Computing in the Continuum: Combining Pervasive Devices and Services to Support Data-Driven Applications. ICDCS 2017: 1815-1824 - [c189]Scott Klasky, Eric Suchyta, Mark Ainsworth, Qing Liu, Ben Whitney, Matthew Wolf, Jong Youl Choi, Ian T. Foster, Mark Kim, Jeremy Logan, Kshitij Mehta, Todd Munson, George Ostrouchov, Manish Parashar, Norbert Podhorszki, David Pugmire, Lipeng Wan:
Exacution: Enhancing Scientific Data Management for Exascale. ICDCS 2017: 1927-1937 - [c188]Eduard Gibert Renart, Javier Diaz Montes, Manish Parashar:
Data-Driven Stream Processing at the Edge. ICFEC 2017: 31-40 - [c187]Mehmet Fatih Aktas, Javier Diaz Montes, Ivan Rodero, Manish Parashar:
WA-Dataspaces: Exploring the Data Staging Abstractions for Wide-Area Distributed Scientific Workflows. ICPP 2017: 251-260 - [c186]Daihou Wang, Eun-Sung Jung, Rajkumar Kettimuthu, Ian T. Foster, David J. Foran, Manish Parashar:
Supporting Real-Time Jobs on the IBM Blue Gene/Q: Simulation-Based Study. JSSPP 2017: 83-102 - [c185]Eduard Gibert Renart, Daniel Balouek-Thomert, Manish Parashar:
Pulsar: Enabling Dynamic Data-Driven IoT Applications. FAS*W@SASO/ICCAC 2017: 357-359 - [c184]Francesc-Xavier Puig, Juan J. Villalobos, Ivan Rodero, Manish Parashar:
Exploring the Potential of FreeBSD Virtualization in Containerized Environments. UCC 2017: 191-192 - 2016
- [j95]Javier Diaz Montes, Ioan Petri, Omer F. Rana, Manish Parashar:
Special Issue on Autonomic Clouds. IEEE Cloud Comput. 3(3): 26-29 (2016) - [j94]Mehmet Fatih Aktas, Georgiana Haldeman, Manish Parashar:
Scheduling and flexible control of bandwidth and in-transit services for end-to-end application workflows. Future Gener. Comput. Syst. 56: 284-294 (2016) - [c183]Mengsong Zou, Javier Diaz Montes, Kiran Nagaraja, Nimish Radia, Manish Parashar:
D3W: Towards Self-Management of Distributed Data-Driven Workflows with QoS Guarantees. CLOUD 2016: 148-155 - [c182]Ivan Rodero, Manish Parashar, Aaditya G. Landge, Sidharth Kumar, Valerio Pascucci, Peer-Timo Bremer:
Evaluation of In-Situ Analysis Strategies at Scale for Power Efficiency and Scalability. CCGrid 2016: 156-164 - [c181]Alejandro Pelaez, Andres Quiroz, Manish Parashar:
Dynamic Adaptation of Policies Using Machine Learning. CCGrid 2016: 501-510 - [c180]E. Wes Bethel, Martin Greenwald, Kerstin Kleese van Dam, Manish Parashar, Stefan M. Wild, H. Steven Wiley:
Management, analysis, and visualization of experimental and observational data - The convergence of data and computing. eScience 2016: 213-222 - [c179]Melissa Romanus, Fan Zhang, Tong Jin, Qian Sun, Hoang Bui, Manish Parashar, Jong Youl Choi, Saloman Janhunen, Robert Hager, Scott Klasky, Choong-Seock Chang, Ivan Rodero:
Persistent Data Staging Services for Data Intensive In-situ Scientific Workflows. DIDC@HPDC 2016: 37-44 - [c178]Jianwu Wang, Moustafa AbdelBaky, Javier Diaz Montes, Shweta Purawat, Manish Parashar, Ilkay Altintas:
Kepler + CometCloud: Dynamic Scientific Workflow Execution on Federated Cloud Resources. ICCS 2016: 700-711 - [c177]Marc Gamell, Daniel S. Katz, Keita Teranishi, Michael A. Heroux, Rob F. Van der Wijngaart, Timothy G. Mattson, Manish Parashar:
Evaluating Online Global Recovery with Fenix Using Application-Aware In-Memory Checkpointing Techniques. ICPP Workshops 2016: 346-355 - [c176]Qian Sun, Melissa Romanus, Tong Jin, Hongfeng Yu, Peer-Timo Bremer, Steve Petruzza, Scott Klasky, Manish Parashar:
In-Staging Data Placement for Asynchronous Coupling of Task-Based Scientific Workflows. ESPM2@SC 2016: 2-9 - [c175]Mengsong Zou, Ali Reza Zamani, Javier Diaz Montes, Ioan Petri, Omer F. Rana, Manish Parashar:
Leveraging In-Transit Computational Capabilities in Federated Ecosystems. SOSE 2016: 81-90 - [c174]Rafael Tolosana-Calasanz, Javier Diaz Montes, Luiz F. Bittencourt, Omer F. Rana, Manish Parashar:
Capacity management for streaming applications over cloud infrastructures with micro billing models. UCC 2016: 251-256 - [e24]Manish Parashar, Hemant K. Jain, Hai Jin:
2016 IEEE International Conference on Mobile Services, MS 2016, San Francisco, CA, USA, June 27 - July 2, 2016. IEEE Computer Society 2016, ISBN 978-1-5090-2625-8 [contents] - 2015
- [j93]K. Selçuk Candan, Christian S. Jensen, Manish Parashar, Kyung Dong Ryu, Heonyoung Yeom:
Cloud Engineering [Guest editors' introduction]. IEEE Cloud Comput. 2(5): 6-8 (2015) - [j92]Solomon Lasluisa, Fan Zhang, Tong Jin, Ivan Rodero, Hoang Bui, Manish Parashar:
In-situ feature-based objects tracking for data-intensive scientific and enterprise analytics workflows. Clust. Comput. 18(1): 29-40 (2015) - [j91]Magdalena Punceva, Ivan Rodero, Manish Parashar, Omer F. Rana, Ioan Petri:
Incentivising resource sharing in social clouds. Concurr. Comput. Pract. Exp. 27(6): 1483-1497 (2015) - [j90]Ciprian Docan, Fan Zhang, Tong Jin, Hoang Bui, Qian Sun, Julian C. Cummings, Norbert Podhorszki, Scott Klasky, Manish Parashar:
ActiveSpaces: Exploring dynamic code deployment for extreme scale data processing. Concurr. Comput. Pract. Exp. 27(14): 3724-3745 (2015) - [j89]Georgiana Haldeman, Ivan Rodero, Manish Parashar, Sabela Ramos, Eddy Z. Zhang, Ulrich Kremer:
Exploring energy-performance-quality tradeoffs for scientific workflows with in-situ data analyses. Comput. Sci. Res. Dev. 30(2): 207-218 (2015) - [j88]Guido Araujo, Jean-Luc Gaudiot, Manish Parashar, Derek Chiou, José Nelson Amaral, Chita R. Das:
Guest Editorial: SBAC-PAD 2013. Int. J. Parallel Program. 43(6): 961-964 (2015) - [j87]Javier Diaz Montes, Moustafa AbdelBaky, Mengsong Zou, Manish Parashar:
CometCloud: Enabling Software-Defined Federations for End-to-End Application Workflows. IEEE Internet Comput. 19(1): 69-73 (2015) - [j86]Ioan Petri, Javier Diaz Montes, Mengsong Zou, Tom Beach, Omer F. Rana, Manish Parashar:
Market Models for Federated Clouds. IEEE Trans. Cloud Comput. 3(3): 398-410 (2015) - [j85]Thomas H. Beach, Omer F. Rana, Yacine Rezgui, Manish Parashar:
Governance Model for Cloud Computing in Building Information Management. IEEE Trans. Serv. Comput. 8(2): 314-327 (2015) - [c173]Manish Parashar, Moustafa AbdelBaky, Mengsong Zou, Ali Reza Zamani, Javier Diaz Montes:
Realizing the Potential of IoT Using Software-Defined Ecosystems. CLOUD 2015: 1149-1158 - [c172]Manuel Diaz-Granados, Javier Diaz Montes, Manish Parashar:
Investigating insurance fraud using social media. IEEE BigData 2015: 1344-1349 - [c171]Ioan Petri, Mengsong Zou, Ali Reza Zamani, Javier Diaz Montes, Omer F. Rana, Manish Parashar:
Integrating Software Defined Networks within a Cloud Federation. CCGRID 2015: 179-188 - [c170]Moustafa AbdelBaky, Javier Diaz Montes, Mengsong Zou, Manish Parashar:
A Framework for Realizing Software-Defined Federations for Scientific Workflows. BigSystem@HPDC 2015: 7-14 - [c169]Marc Gamell, Keita Teranishi, Michael A. Heroux, Jackson Mayo, Hemanth Kolla, Jacqueline Chen, Manish Parashar:
Exploring Failure Recovery for Stencil-based Applications at Extreme Scales. HPDC 2015: 279-282 - [c168]Daihou Wang, David J. Foran, Xin Qi, Manish Parashar:
HetroCV: Auto-tuning Framework and Runtime for Image Processing and Computer Vision Applications on Heterogeneous Platform. ICPP Workshops 2015: 119-128 - [c167]Ioan Petri, Javier Diaz Montes, Omer F. Rana, Yacine Rezgui, Manish Parashar, Luiz F. Bittencourt:
Coordinating Data Analysis and Management in Multi-layered Clouds. IoT 360 (1) 2015: 357-366 - [c166]Tong Jin, Fan Zhang, Qian Sun, Hoang Bui, Melissa Romanus, Norbert Podhorszki, Scott Klasky, Hemanth Kolla, Jacqueline Chen, Robert Hager, Choong-Seock Chang, Manish Parashar:
Exploring Data Staging Across Deep Memory Hierarchies for Coupled Data Intensive Simulation Workflows. IPDPS 2015: 1033-1042 - [c165]