Explanipedia

UnifyFL: Enabling Decentralized Cross-Silo Federated Learning Open

S Sarang, Druva Dhakshinamoorthy, Aditya Sharma, Yuvraj Singh Bhadauria, S. Vivek , et al. · 2025

Federated Learning (FL) is a decentralized machine learning (ML) paradigm in which models are trained on private data across several devices called clients and combined at a single node called an aggregator rather than aggregating the data…

Benchmarking Mutual Information-based Loss Functions in Federated Learning Open

S. Bhola Sarang, Harsh D. Chothani, Ahmed M. Abdelmoniem, Arnab K. Paul · 2025

Federated Learning (FL) has attracted considerable interest due to growing privacy concerns and regulations like the General Data Protection Regulation (GDPR), which stresses the importance of privacy-preserving and fair machine learning a…

Factors Affecting the Duration of Hospital Stay in Newborn with Hyperbilirubinemia Admitted in a Tertiary Care Pediatric Hospital of Kolkata Open

Nenavath Jeevan Naik, Manisha De, Arnab K. Paul, Hema Namdeo, Srinivas Kowshik Malluri · 2025

Introduction: Despite being a temporary condition, neonatal jaundice is still the most common cause of hospitalization in the first week of life. Physiological jaundice is due to the developmental insufficiency of bilirubin uptake, transpo…

When Less is More: Achieving Faster Convergence in Distributed Edge Machine Learning Open

Advik Raj Basani, S. Vivek, Advaith Krishna, Arnab K. Paul · 2024

Distributed Machine Learning (DML) on resource-constrained edge devices holds immense potential for real-world applications. However, achieving fast convergence in DML in these heterogeneous environments remains a significant challenge. Tr…

Tarazu: An Adaptive End-to-end I/O Load-balancing Framework for Large-scale Parallel File Systems Open

Arnab K. Paul, Sarah Neuwirth, Bharti Wadhwa, Feiyi Wang, Sarp Oral , et al. · 2024

The imbalanced I/O load on large parallel file systems affects the parallel I/O performance of high-performance computing (HPC) applications. One of the main reasons for I/O imbalances is the lack of a global view of system-wide resource c…

An End-to-end High-performance Deduplication Scheme for Docker Registries and Docker Container Storage Systems Open

Nannan Zhao, Muhui Lin, Hadeel Albahar, Arnab K. Paul, Zhijie Huan , et al. · 2024

The wide adoption of Docker containers for supporting agile and elastic enterprise applications has led to a broad proliferation of container images. The associated storage performance and capacity requirements place a high pressure on the…

Analyzing File Access Patterns on Large-Scale HPC Systems: Opportunities for File Prefetching Open

Ahmad Maroof Karimi, Arnab K. Paul, Jong Youl Choi, Lipeng Wan, Feiyi Wang · 2023

This paper explores the potential opportunities for implementing file prefetching techniques on large-scale high-performance computing (HPC) systems. Specifically, we investigate the file access patterns of various applications across mult…

Role of Sildenafil in Severe COVID-19 Pneumonia in Infancy - A Case Series Open

Jayant Kumar Muduli, Meenakshi Mitra, Asish Banerjee, Arnab K. Paul · 2022

SARS-CoV-2 virus primarily affects the respiratory system, although other organ systems are also involved. Though pulmonary arterial hypertension (PAH) has been described in as a sequela of COVID pneumonia in adults, only a coincidental as…

I/O performance analysis of machine learning workloads on leadership scale supercomputer Open

Ahmad Maroof Karimi, Arnab K. Paul, Feiyi Wang · 2022

Hvac: Removing I/O Bottleneck for Large-Scale Deep Learning Applications Open

Awais Khan, Arnab K. Paul, Christopher Zimmer, Sarp Oral, Sajal Dash , et al. · 2022

Scientific communities are increasingly adopting deep learning (DL) models in their applications to accelerate scientific discovery processes. However, with rapid growth in the computing capabilities of HPC supercomputers, large-scale DL a…

Machine Learning Assisted HPC Workload Trace Generation for Leadership Scale Storage Systems Open

Arnab K. Paul, Jong Youl Choi, Ahmad Maroof Karimi, Feiyi Wang · 2022

Monitoring and analyzing a wide range of I/O activities in an HPC cluster is important in maintaining mission-critical performance in a large-scale, multi-user, parallel storage system. Center-wide I/O traces can provide high-level informa…

Access Patterns and Performance Behaviors of Multi-layer Supercomputer I/O Subsystems under Production Load Open

Jean Luca Bez, Ahmad Maroof Karimi, Arnab K. Paul, Bing Xie, Suren Byna , et al. · 2022

Scientific computing workloads at HPC facilities have been shifting from traditional numerical simulations to AI/ML applications for training and inference while processing and producing ever-increasing amounts of scientific data. To addre…

Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing Open

Pravallika Devineni, Panchapakesan Ganesh, Nikhil Sivadas, Abhijeet Dhakane, Ketan Maheshwari , et al. · 2022

April 2020 Darshan counters from the Summit supercomputer Open

Ahmad Maroof Karimi, Bing Xie, Arnab K. Paul, Sarp Oral, Feiyi Wang · 2022

This dataset is the Darshan counters collected from the Summit supercomputer in a month of April 2020. 1. Description of methods used for collection/generation of data: Job submitted on Summit HPC system when completed successfully and has…

Characterizing Machine Learning I/O Workloads on Leadership Scale HPC Systems Open

Arnab K. Paul, Ahmad Maroof Karimi, Feiyi Wang · 2021

High performance computing (HPC) is no longer solely limited to traditional workloads such as simulation and modeling. With the increase in the popularity of machine learning (ML) and deep learning (DL) technologies, we are observing that …

Table of Contents Open

Debasmita Biswas, Virginia Tech, Sarah Neuwirth, Arnab K. Paul · 2021

Parallel I/O Evaluation Techniques and Emerging HPC Workloads: A Perspective Open

Sarah Neuwirth, Arnab K. Paul · 2021

Emerging workloads such as artificial intelligence, big data analytics and complex multi-step workflows alongside future exascale applications are anticipated future HPC workloads, which will result in a more diverse I/O system workload an…

SMC 2021 Data Challenge: Analyzing Resource Utilization and User Behavior on Titan Supercomputer Open

Sajal Dash, Arnab K. Paul, Sarp Oral, Feiyi Wang · 2021

Resource utilization statistics of submitted jobs on a supercomputer can help us understand how users from various scientific domains use HPC platforms and better design a job scheduler. We explore to generate insight regarding workload di…

Understanding HPC Application I/O Behavior Using System Level Statistics Open

Arnab K. Paul, Olaf Faaland, Adam Moody, Elsa Gonsiorowski, Kathryn Mohror , et al. · 2020

The processor performance of high performance computing (HPC) systems is increasing at a much higher rate than storage performance. This imbalance leads to I/O performance bottlenecks in massively parallel HPC applications. Therefore, ther…

An Application-Attuned Framework for Optimizing HPC Storage Systems Open

Arnab K. Paul · 2020

High performance computing (HPC) is routinely employed in diverse domains such as life sciences, and Geology, to simulate and understand the behavior of complex phenomena. Big data driven scientific simulations are resource intensive and r…

Generalized Weighted Exponential Similarity Measures of Single Valued Neutrosophic Sets Open

Abhijit Saha, Arnab K. Paul · 2019

In this paper, we introduce some new generalized weighted similarity measures based on the exponential functions defined on truth-membership function, indeterminacy membership function and falsity membership function of a single valued neu…

Generalized Weighted Exponential Similarity Measures of Single Valued Neutrosophic Sets Open

Abhijit Saha, Arnab K. Paul · 2019

Generalized Weighted Exponential Similarity Measures of Single Valued Neutrosophic Sets Open

Abhijit Saha, Arnab K. Paul · 2019

iez: Resource Contention Aware Load Balancing for Large-Scale Parallel File Systems Open

Bharti Wadhwa, Arnab K. Paul, Sarah Neuwirth, Feiyi Wang, Sarp Oral , et al. · 2019

Parallel I/O performance is crucial to sustaining scientific applications on large-scale High-Performance Computing (HPC) systems. However, I/O load imbalance in the underlying distributed and shared storage systems can significantly reduc…

I/O load balancing for big data HPC applications Open

Arnab K. Paul, Arpit Goyal, Feiyi Wang, Sarp Oral, Ali R. Butt , et al. · 2017

High Performance Computing (HPC) big data problems require efficient distributed storage systems. However, at scale, such storage systems often experience load imbalance and resource contention due to two factors: the bursty nature of scie…

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