CHOPPER: Optimizing Data Partitioning for In-memory Data Analytics Frameworks. - Arnab Kumar Paul; Wenjie Zhuang; Luna Xu; Min Li; M. Mustafa Rafique; Ali Raza Butt (CLUSTER, 2016)

I/O load balancing for big data HPC applications. - Arnab Kumar Paul; Arpit Goyal; Feiyi Wang; Sarp Oral; Ali Raza Butt; Michael J. Brim; Sangeetha B. Srinivasa (IEEE BigData, 2017)

Toward scalable monitoring on large-scale storage for software defined cyberinfrastructure. - Arnab Kumar Paul; Steven Tuecke; Ryan Chard; Ali Raza Butt; Kyle Chard; Ian T. Foster (PDSW-DISCS@SC, 2017)

FSMonitor: Scalable File System Monitoring for Arbitrary Storage Systems. - Arnab Kumar Paul; Ryan Chard; Kyle Chard; Steven Tuecke; Ali Raza Butt; Ian T. Foster (CLUSTER, 2019)

Cslim: automated extraction of IoT functionalities from legacy C codebases. - Hyogi Sim; Arnab Kumar Paul; Eli Tilevich; Ali Raza Butt; Muhammad Shahzad 001 (ICDCN, 2019)

iez: Resource Contention Aware Load Balancing for Large-Scale Parallel File Systems. - Bharti Wadhwa; Arnab Kumar Paul; Sarah Neuwirth; Feiyi Wang; Sarp Oral; Ali Raza Butt; Jon Bernard; Kirk W. Cameron (IPDPS, 2019)

On the Use of Containers in High Performance Computing Environments. - Subil Abraham; Arnab Kumar Paul; Redwan Ibne Seraj Khan; Ali Raza Butt (CLOUD, 2020)

Efficient Metadata Indexing for HPC Storage Systems. - Arnab Kumar Paul; Brian Wang; Nathan Rutman; Cory Spitz; Ali Raza Butt (CCGRID, 2020)

Understanding HPC Application I/O Behavior Using System Level Statistics. - Arnab Kumar Paul; Olaf Faaland; Adam Moody; Elsa Gonsiorowski; Kathryn M. Mohror; Ali Raza Butt (HiPC, 2020)

Stargazer: A Deep Learning Approach for Estimating the Performance of Edge- Based Clustering Applications. - Breno Dantas Cruz; Arnab Kumar Paul; Zheng Song 001; Eli Tilevich (SMDS, 2020)

An Application-Attuned Framework for Optimizing HPC Storage Systems. - Arnab Kumar Paul (2020)

Parallel I/O Evaluation Techniques and Emerging HPC Workloads: A Perspective. - Sarah Neuwirth; Arnab Kumar Paul (CLUSTER, 2021)

Bridging Network and Parallel I/O Research for Improving Data-Intensive Distributed Applications. - Debasmita Biswas; Sarah Neuwirth; Arnab Kumar Paul; Ali Raza Butt (INDIS@SC, 2021)

Characterizing Machine Learning I/O Workloads on Leadership Scale HPC Systems. - Arnab Kumar Paul; Ahmad Maroof Karimi; Feiyi Wang (MASCOTS, 2021)

Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. - Pravallika Devineni; Panchapakesan Ganesh; Nikhil Sivadas; Abhijeet Dhakane; Ketan Maheshwari; Drahomira Herrmannova; Ramakrishnan Kannan; Seung-Hwan Lim; Thomas E. Potok; Jordan B. Chipka; Priyantha Mudalige; Mark Coletti; et al. (SMC, 2021)

Large-Scale Analysis of Docker Images and Performance Implications for Container Storage Systems. - Nannan Zhao; Vasily Tarasov; Hadeel Albahar; Ali Anwar 001; Lukas Rupprecht; Dimitrios Skourtis; Arnab Kumar Paul; Keren Chen; Ali Raza Butt (IEEE Trans. Parallel Distributed Syst., 2021)

SchedTune: A Heterogeneity-Aware GPU Scheduler for Deep Learning. - Hadeel Albahar; Shruti Dongare; Yanlin Du; Nannan Zhao; Arnab Kumar Paul; Ali Raza Butt (CCGRID, 2022)

Hvac: Removing I/O Bottleneck for Large-Scale Deep Learning Applications. - Awais Khan 002; Arnab K. Paul; Christopher Zimmer 001; Sarp Oral; Sajal Dash; Scott Atchley; Feiyi Wang (CLUSTER, 2022)

Access Patterns and Performance Behaviors of Multi-layer Supercomputer I/O Subsystems under Production Load. - Jean Luca Bez; Ahmad Maroof Karimi; Arnab Kumar Paul; Bing Xie; Suren Byna; Philip H. Carns; Sarp Oral; Feiyi Wang; Jesse Hanley (HPDC, 2022)

Machine Learning Assisted HPC Workload Trace Generation for Leadership Scale Storage Systems. - Arnab K. Paul; Jong Youl Choi; Ahmad Maroof Karimi; Feiyi Wang (HPDC, 2022)

I/O performance analysis of machine learning workloads on leadership scale supercomputer. - Ahmad Maroof Karimi; Arnab K. Paul; Feiyi Wang (Perform. Evaluation, 2022)

An I/O Performance Evaluation of Varying CephFS Striping Patterns. - Debasmita Biswas; Sarah Neuwirth; Arnab K. Paul; Ali Raza Butt (CLUSTER Workshops, 2023)

Does Varying BeeGFS Configuration Affect the I/O Performance of HPC Workloads? - Arnav Borkar; Joel Tony; Hari Vamsi K. N; Tushar Barman; Yash Bhisikar; Sreenath T. M.; Arnab K. Paul (CLUSTER Workshops, 2023)

SHADE: Enable Fundamental Cacheability for Distributed Deep Learning Training. - Redwan Ibne Seraj Khan; Ahmad Hossein Yazdani; Yuqi Fu; Arnab K. Paul; Bo Ji 001; Xun Jian 002; Yue Cheng 001; Ali Raza Butt (FAST, 2023)

HiPC 2023 Student Research Symposium (HiPC SRS 2023). - Arnab K. Paul; Suren Byna (HiPCW, 2023)

Characteristics of Deep Learning Workloads in Industry, Academic Institutions and National Laboratories. - Natasha Meena Joseph; S. Sai Vineet; Kunal Korgaonkar; Arnab K. Paul (ICDCN, 2023)

A Data-Centric Approach for Analyzing Large-Scale Deep Learning Applications. - S. Sai Vineet; Natasha Meena Joseph; Kunal Korgaonkar; Arnab K. Paul (ICDCN, 2023)

Modeling the Impact of System-Level Parameters on I/O Performance of HPC Applications. - Debasmita Biswas; Arnab K. Paul; Sarah Neuwirth; Ali Raza Butt (MASCOTS, 2023)

Analyzing File Access Patterns on Large-Scale HPC Systems: Opportunities for File Prefetching. - Ahmad Maroof Karimi; Arnab K. Paul; Jong Youl Choi; Lipeng Wan 001; Feiyi Wang (MASCOTS, 2023)

FedCaSe: Enhancing Federated Learning with Heterogeneity-aware Caching and Scheduling. - Redwan Ibne Seraj Khan; Arnab K. Paul; Yue Cheng 001; Xun Steve Jian; Ali Raza Butt (SoCC, 2024)

Studying the Effects of Asynchronous I/O on HPC I/O Patterns. - Arnav Gupta; Druva Dhakshinamoorthy; Arnab K. Paul (CLUSTER Workshops, 2024)

When Less is More: Achieving Faster Convergence in Distributed Edge Machine Learning. - Advik Raj Basani; Siddharth Chaitra Vivek; Advaith Krishna; Arnab K. Paul (HiPC, 2024)

Towards Pre-Training Data Evaluation for Client Selection in Federated Learning. - Vijay Dharmaji; Manit Tanwar; Subroto Majumder; M. Mustafa Rafique; Arnab K. Paul (HIPCW, 2024)

Understanding Infrastructure Drift in Federated Learning Systems. - Shashank Rana; Vimarsh Shah; Aishwarya Jayashankar; Ayush Bhardwaj; Arnab K. Paul (HIPCW, 2024)

Tarazu: An Adaptive End-to-end I/O Load-balancing Framework for Large-scale Parallel File Systems. - Arnab K. Paul; Sarah Neuwirth; Bharti Wadhwa; Feiyi Wang; Sarp Oral; Ali Raza Butt (ACM Trans. Storage, 2024)

An End-to-end High-performance Deduplication Scheme for Docker Registries and Docker Container Storage Systems. - Nannan Zhao; Muhui Lin; Hadeel Albahar; Arnab K. Paul; Zhijie Huan; Subil Abraham; Keren Chen; Vasily Tarasov; Dimitrios Skourtis; Ali Anwar 001; Ali Raza Butt (ACM Trans. Storage, 2024)

Scheduling Big Machine Learning Tasks on Clusters of Heterogeneous Edge Devices. - Saumya Mathkar; Shreya Aiyer; Yashovardhan Bapat; Pinki Pinki; Arnab K. Paul; Vinayak Naik (COMSNETS, 2025)

User-based I/O Profiling for Leadership Scale HPC Workloads. - Ahmad Hossein Yazdani; Arnab K. Paul; Ahmad Maroof Karimi; Feiyi Wang; Ali Raza Butt (ICDCN, 2025)

A Blockchain-Enabled Framework for Storage and Retrieval of Social Data. - Aishwarya Parab; Prakhar Pradhan; Yogesh Simmhan; Arnab K. Paul (CoRR, 2025)

Benchmarking Mutual Information-based Loss Functions in Federated Learning. - Sarang S; Harsh D. Chothani; Qilei Li; Ahmed M. Abdelmoniem; Arnab K. Paul (CoRR, 2025)

UnifyFL: Enabling Decentralized Cross-Silo Federated Learning. - Sarang S; Druva Dhakshinamoorthy; Aditya Shiva Sharma; Yuvraj Singh Bhadauria; Siddharth Chaitra Vivek; Arihant Bansal; Arnab K. Paul (CoRR, 2025)