Pradeep Subedi

According to our database, Pradeep Subedi authored at least 30 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Residual-INR: Communication Efficient On-Device Learning Using Implicit Neural Representation.

Hanqiu Chen, Xuebin Yao, Pradeep Subedi, Cong Hao

CoRR, 2024

ICGMM: CXL-enabled Memory Expansion with Intelligent Caching Using Gaussian Mixture Model.

Hanqiu Chen, Yitu Wang, Luis Vitório Cargnini, Mohammadreza Soltaniyeh, Dongyang Li, Gongjin Sun, Pradeep Subedi, Andrew Chang, Yiran Chen, Cong Hao

Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

2023

Adaptive elasticity policies for staging-based <i>in situ</i> visualization.

Zhe Wang, Matthieu Dorier, Pradeep Subedi, Philip E. Davis, Manish Parashar

Future Gener. Comput. Syst., May, 2023

SRC: Mitigate I/O Throughput Degradation in Network Congestion Control of Disaggregated Storage Systems.

Danlin Jia, Yiming Xie, Li Wang, Xiaoqian Zhang, Allen Yang, Xuebin Yao, Mahsa Bayati, Pradeep Subedi, Bo Sheng, Ningfang Mi

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

DIRS: Dynamic Initial Rate Setting in Congestion Control for Disaggregated Storage Systems.

Xiaoqian Zhang, Allen Yang, Danlin Jia, Li Wang, Mahsa Bayati, Pradeep Subedi, Xuebin Yao, Bo Sheng, Ningfang Mi

Proceedings of the International Conference on Computing, Networking and Communications, 2023

Benesh: a Framework for Choreographic Coordination of In Situ Workflows.

Philip E. Davis, Jacob S. Merson, Pradeep Subedi, Lee F. Ricketson, Cameron W. Smith, Mark S. Shephard, Manish Parashar

Proceedings of the 30th IEEE International Conference on High Performance Computing, 2023

2022

The Exascale Framework for High Fidelity coupled Simulations (EFFIS): Enabling whole device modeling in fusion science.

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

Int. J. High Perform. Comput. Appl., 2022

Assembling Portable In-Situ Workflow from Heterogeneous Components using Data Reorganization.

Bo Zhang, Pradeep Subedi, Philip E. Davis, Francesco Rizzi, Keita Teranishi, Manish Parashar

Proceedings of the 22nd IEEE International Symposium on Cluster, 2022

2021

Exploring the Role of Machine Learning in Scientific Workflows: Opportunities and Challenges.

Azita Nouri, Philip E. Davis, Pradeep Subedi, Manish Parashar

CoRR, 2021

Strategies for Democratization of Supercomputing: Availability, Accessibility and Usability of High Performance Computing for Education and Practice of Big Data Analytics.

Jim Samuel, Margaret Brennan-Tonetta, Yana Samuel, Pradeep Subedi, Jack Smith

CoRR, 2021

An Adaptive Elasticity Policy For Staging Based In-Situ Processing.

Zhe Wang, Matthieu Dorier, Pradeep Subedi, Philip E. Davis, Manish Parashar

Proceedings of the 2021 IEEE Workshop on Workflows in Support of Large-Scale Science (WORKS), 2021

Facilitating Staging-based Unstructured Mesh Processing to Support Hybrid In-Situ Workflows.

Zhe Wang, Pradeep Subedi, Matthieu Dorier, Philip E. Davis, Manish Parashar

Proceedings of the IEEE International Parallel and Distributed Processing Symposium Workshops, 2021

Adaptive Placement of Data Analysis Tasks For Staging Based In-Situ Processing.

Zhe Wang, Pradeep Subedi, Matthieu Dorier, Philip E. Davis, Manish Parashar

Proceedings of the 28th IEEE International Conference on High Performance Computing, 2021

RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows.

Pradeep Subedi, Philip E. Davis, Manish Parashar

Proceedings of the IEEE International Conference on Cluster Computing, 2021

2020

CoREC: Scalable and Resilient In-memory Data Staging for In-situ Workflows.

Shaohua Duan, Pradeep Subedi, Philip E. Davis, Keita Teranishi, Hemanth Kolla, Marc Gamell, Manish Parashar

ACM Trans. Parallel Comput., 2020

Exploring Trade-offs in Dynamic Task Triggering for Loosely Coupled Scientific Workflows.

Zhe Wang, Pradeep Subedi, Shaohua Duan, Yubo Qin, Philip E. Davis, Anthony Simonet, Ivan Rodero, Manish Parashar

CoRR, 2020

Benesh: a Programming Model for Coupled Scientific Workflows.

Philip E. Davis, Pradeep Subedi, Shaohua Duan, Lee F. Ricketson, Jeffrey A. F. Hittinger, Manish Parashar

Proceedings of the 5th IEEE/ACM International Workshop on Extreme Scale Programming Models and Middleware, 2020

Staging Based Task Execution for Data-driven, In-Situ Scientific Workflows.

Zhe Wang, Pradeep Subedi, Matthieu Dorier, Philip E. Davis, Manish Parashar

Proceedings of the IEEE International Conference on Cluster Computing, 2020

2019

Addressing data resiliency for staging based scientific workflows.

Shaohua Duan, Pradeep Subedi, Philip E. Davis, Manish Parashar

Proceedings of the International Conference for High Performance Computing, 2019

Leveraging Machine Learning for Anticipatory Data Delivery in Extreme Scale In-situ Workflows.

Pradeep Subedi, Philip E. Davis, Manish Parashar

Proceedings of the 2019 IEEE International Conference on Cluster Computing, 2019

2018

Using Intel Optane Devices for In-situ Data Staging in HPC Workflows.

Pradeep Subedi, Philip E. Davis, Juan J. Villalobos, Ivan Rodero, Manish Parashar

CoRR, 2018

Stacker: an autonomic data movement engine for extreme-scale data staging-based in-situ workflows.

Pradeep Subedi, Philip E. Davis, Shaohua Duan, Scott Klasky, Hemanth Kolla, Manish Parashar

Proceedings of the International Conference for High Performance Computing, 2018

Exploring Power Budget Scheduling Opportunities and Tradeoffs for AMR-Based Applications.

Yubo Qin, Ivan Rodero, Pradeep Subedi, Manish Parashar, Sandro Rigo

Proceedings of the 30th International Symposium on Computer Architecture and High Performance Computing, 2018

Scalable Data Resilience for In-memory Data Staging.

Shaohua Duan, Pradeep Subedi, Keita Teranishi, Philip E. Davis, Hemanth Kolla, Marc Gamell, Manish Parashar

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018

2016

CoARC: Co-operative, Aggressive Recovery and Caching for Failures in Erasure Coded Hadoop.

Pradeep Subedi, Ping Huang, Tong Liu, Joseph Moore, Stan Skelton, Xubin He

Proceedings of the 45th International Conference on Parallel Processing, 2016

2015

FINGER: A novel erasure coding scheme using fine granularity blocks to improve Hadoop write and update performance.

Pradeep Subedi, Ping Huang, Benjamin Young, Xubin He

Proceedings of the 10th IEEE International Conference on Networking, 2015

PPM: A Partitioned and Parallel Matrix Algorithm to Accelerate Encoding/Decoding Process of Asymmetric Parity Erasure Codes.

Shiyi Li, Qiang Cao, Shenggang Wan, Wenhui Zhang, Changsheng Xie, Xubin He, Pradeep Subedi

Proceedings of the 44th International Conference on Parallel Processing, 2015

2014

FlexECC: Partially Relaxing ECC of MLC SSD for Better Cache Performance.

Ping Huang, Pradeep Subedi, Xubin He, Shuang He, Ke Zhou

Proceedings of the 2014 USENIX Annual Technical Conference, 2014

A hybrid erasure-coded ECC scheme to improve performance and reliability of solid state drives.

Pradeep Subedi, Ping Huang, Xubin He, Ming Zhang, Jizhong Han

Proceedings of the IEEE 33rd International Performance Computing and Communications Conference, 2014

2013

A Comprehensive Analysis of XOR-Based Erasure Codes Tolerating 3 or More Concurrent Failures.

Pradeep Subedi, Xubin He

Proceedings of the 2013 IEEE International Symposium on Parallel & Distributed Processing, 2013