A Comprehensive Analysis of XOR-Based Erasure Codes Tolerating 3 or More Concurrent Failures. - Pradeep Subedi; Xubin He (IPDPS Workshops, 2013)

A hybrid erasure-coded ECC scheme to improve performance and reliability of solid state drives. - Pradeep Subedi; Ping Huang 001; Xubin He; Ming Zhang 026; Jizhong Han (IPCCC, 2014)

FlexECC: Partially Relaxing ECC of MLC SSD for Better Cache Performance. - Ping Huang 001; Pradeep Subedi; Xubin He; Shuang He; Ke Zhou 001 (USENIX ATC, 2014)

PPM: A Partitioned and Parallel Matrix Algorithm to Accelerate Encoding/Decoding Process of Asymmetric Parity Erasure Codes. - Shiyi Li; Qiang Cao 001; Shenggang Wan; Wenhui Zhang 005; Changsheng Xie; Xubin He; Pradeep Subedi (ICPP, 2015)

FINGER: A novel erasure coding scheme using fine granularity blocks to improve Hadoop write and update performance. - Pradeep Subedi; Ping Huang 001; Benjamin Young; Xubin He (NAS, 2015)

CoARC: Co-operative, Aggressive Recovery and Caching for Failures in Erasure Coded Hadoop. - Pradeep Subedi; Ping Huang 001; Tong Liu; Joseph Moore; Stan Skelton; Xubin He (ICPP, 2016)

Scalable Data Resilience for In-memory Data Staging. - Shaohua Duan; Pradeep Subedi; Keita Teranishi; Philip E. Davis; Hemanth Kolla; Marc Gamell; Manish Parashar (IPDPS, 2018)

Exploring Power Budget Scheduling Opportunities and Tradeoffs for AMR-Based Applications. - Yubo Qin; Ivan Rodero; Pradeep Subedi; Manish Parashar; Sandro Rigo (SBAC-PAD, 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 (SC, 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)

Leveraging Machine Learning for Anticipatory Data Delivery in Extreme Scale In-situ Workflows. - Pradeep Subedi; Philip E. Davis; Manish Parashar (CLUSTER, 2019)

Addressing data resiliency for staging based scientific workflows. - Shaohua Duan; Pradeep Subedi; Philip E. Davis; Manish Parashar (SC, 2019)

Staging Based Task Execution for Data-driven, In-Situ Scientific Workflows. - Zhe Wang 059; Pradeep Subedi; Matthieu Dorier; Philip E. Davis; Manish Parashar (CLUSTER, 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 (ESPM2@SC, 2020)

Exploring Trade-offs in Dynamic Task Triggering for Loosely Coupled Scientific Workflows. - Zhe Wang 059; Pradeep Subedi; Shaohua Duan; Yubo Qin; Philip E. Davis; Anthony Simonet; Ivan Rodero; Manish Parashar (CoRR, 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)

RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows. - Pradeep Subedi; Philip E. Davis; Manish Parashar (CLUSTER, 2021)

Adaptive Placement of Data Analysis Tasks For Staging Based In-Situ Processing. - Zhe Wang 059; Pradeep Subedi; Matthieu Dorier; Philip E. Davis; Manish Parashar (HiPC, 2021)

Facilitating Staging-based Unstructured Mesh Processing to Support Hybrid In-Situ Workflows. - Zhe Wang 059; Pradeep Subedi; Matthieu Dorier; Philip E. Davis; Manish Parashar (IPDPS Workshops, 2021)

An Adaptive Elasticity Policy For Staging Based In-Situ Processing. - Zhe Wang 059; Matthieu Dorier; Pradeep Subedi; Philip E. Davis; Manish Parashar (WORKS, 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)

Exploring the Role of Machine Learning in Scientific Workflows: Opportunities and Challenges. - Azita Nouri; Philip E. Davis; Pradeep Subedi; Manish Parashar (CoRR, 2021)

Assembling Portable In-Situ Workflow from Heterogeneous Components using Data Reorganization. - Bo Zhang 120; Pradeep Subedi; Philip E. Davis; Francesco Rizzi; Keita Teranishi; Manish Parashar (CCGRID, 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 001; Philip E. Davis; Julien Dominski; Stéphane Ethier; Ian T. Foster; Kai Germaschewski; et al. (Int. J. High Perform. Comput. Appl., 2022)

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 (HiPC, 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 (ICNC, 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 (IPDPS, 2023)

Adaptive elasticity policies for staging-based in situ visualization. - Zhe Wang 059; Matthieu Dorier; Pradeep Subedi; Philip E. Davis; Manish Parashar (Future Gener. Comput. Syst., 2023)

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 001; Cong Hao (DAC, 2024)

Residual-INR: Communication Efficient On-Device Learning Using Implicit Neural Representation. - Hanqiu Chen; Xuebin Yao; Pradeep Subedi; Cong Hao (ICCAD, 2024)