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Computer Science

D-Index
33
Citations
4521
World Ranking
12701
National Ranking
5129

Research.com Recognitions

  • 2009 - ACM-IEEE CS George Michael Memorial HPC Fellowships Topology-aware task mapping

Overview

Abhinav Bhatele is affiliated with the University of Maryland, College Park in the United States. Their research primarily focuses on computer science with a notable emphasis on the subfields of computer networks and communications, artificial intelligence, information systems, hardware and architecture, and computer vision and pattern recognition.

The main topics covered in Bhatele's work include parallel computing and optimization techniques, cloud computing and resource management, software system performance and reliability, distributed and parallel computing systems, software engineering research, scientific computing and data management, and advanced neural network applications.

Bhatele has published extensively with a total of 61 publications in computer science. The frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Visualization and Computer Graphics
  • 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
  • IEEE Transactions on Parallel and Distributed Systems

Recent papers authored by Bhatele include:

  • AxoNN: An asynchronous, message-driven parallel framework for extreme-scale deep learning, 2022, 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
  • Scalable Comparative Visualization of Ensembles of Call Graphs, 2021, IEEE Transactions on Visualization and Computer Graphics
  • Resource Utilization Aware Job Scheduling to Mitigate Performance Variability, 2022, 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
  • Transformers Can Do Arithmetic with the Right Embeddings, 2024, arXiv (Cornell University)
  • HPC-Coder: Modeling Parallel Programs using Large Language Models, 2023, arXiv (Cornell University)

Frequent collaborators with Bhatele include:

  • Daniel Nichols
  • Siddharth Singh
  • Tom Goldstein
  • Harshitha Menon
  • John Kirchenbauer

Bhatele's research has been recognized with awards such as the ACM-IEEE CS George Michael Memorial HPC Fellowship in 2009, which specifically cited their work on topology-aware task mapping.

Best Publications

  • Scalable Molecular Dynamics with NAMD.

    James C. Phillips;Klaus Schulten;Abhinav Bhatele;Chao Mei

  • Scalable Molecular Dynamics with NAMD

    J. C. Phillips;K. Schulten;A. Bhatele;C. Mei

  • Exploring Traditional and Emerging Parallel Programming Models Using a Proxy Application

    Ian Karlin;Abhinav Bhatele;Jeff Keasler;Bradford L. Chamberlain

  • There goes the neighborhood: performance degradation due to nearby jobs

    Abhinav Bhatele;Kathryn Mohror;Steven H. Langer;Katherine E. Isaacs

  • Dynamic topology aware load balancing algorithms for molecular dynamics applications

    Abhinav Bhatelé;Laxmikant V. Kalé;Sameer Kumar

  • Scalable molecular dynamics with NAMD on the IBM Blue Gene/L system

    S. Kumar;C. Huang;G. Zheng;E. Bohm

  • Overcoming scaling challenges in biomolecular simulations across multiple platforms

    A. Bhatele;S. Kumar;Chao Mei;J.C. Phillips

  • State of the Art of Performance Visualization

    Katherine E. Isaacs;Alfredo Giménez;Ilir Jusufi;Todd Gamblin

  • Periodic hierarchical load balancing for large supercomputers

    Gengbin Zheng;Abhinav Bhatelé;Esteban Meneses;Laxmikant V. Kalé

  • Avoiding hot-spots on two-level direct networks

    Abhinav Bhatele;Nikhil Jain;William D. Gropp;Laxmikant V. Kale

  • Hierarchical Load Balancing for Charm++ Applications on Large Supercomputers

    Gengbin Zheng;Esteban Meneses;Abhinav Bhatele;Laxmikant V. Kale

  • Maximizing throughput on a dragonfly network

    Nikhil Jain;Abhinav Bhatele;Xiang Ni;Nicholas J. Wright

  • Mapping applications with collectives over sub-communicators on torus networks

    Abhinav Bhatele;Todd Gamblin;Steven H. Langer;Peer-Timo Bremer

  • Fine-grained parallelization of the Car-Parrinello ab initio molecular dynamics method on the IBM Blue Gene/L supercomputer

    E. Bohm;A. Bhatele;L. V. Kalé;M. E. Tuckerman

  • Automated mapping of regular communication graphs on mesh interconnects

    Abhinav Bhatele;Gagan Raj Gupta;Laxmikant V. Kale;I-Hsin Chung

  • Improving communication performance in dense linear algebra via topology aware collectives

    Edgar Solomonik;Abhinav Bhatele;James Demmel

  • Visualizing Network Traffic to Understand the Performance of Massively Parallel Simulations

    A. G. Landge;J. A. Levine;A. Bhatele;K. E. Isaacs

  • Combing the Communication Hairball: Visualizing Parallel Execution Traces using Logical Time

    Katherine E. Isaacs;Peer Timo Bremer;Ilir Jusufi;Todd Gamblin

  • Evaluating HPC networks via simulation of parallel workloads

    Nikhil Jain;Abhinav Bhatele;Sam White;Todd Gamblin

  • Parallel Science and Engineering Applications: The Charm++ Approach

    Laxmikant V. Kale;Laxmikant V. Kale;Abhinav Bhatele

  • Analyzing Network Health and Congestion in Dragonfly-Based Supercomputers

    Abhinav Bhatele;Nikhil Jain;Yarden Livnat;Valerio Pascucci

  • Massively parallel first-principles simulation of electron dynamics in materials

    Erik W. Draeger;Xavier Andrade;John A. Gunnels;Abhinav Bhatele

  • Automating topology aware mapping for supercomputers

    Laxmikant V. Kale;Abhinav Bhatele

  • Predicting application performance using supervised learning on communication features

    Nikhil Jain;Abhinav Bhatele;Michael P. Robson;Todd Gamblin

Frequent Co-Authors

Laxmikant V. Kale
Laxmikant V. Kale University of Illinois at Urbana-Champaign
Martin Schulz
Martin Schulz Technical University of Munich
Peer-Timo Bremer
Peer-Timo Bremer Lawrence Livermore National Laboratory
Bernd Hamann
Bernd Hamann University of California, Davis
Valerio Pascucci
Valerio Pascucci University of Utah
Kwan-Liu Ma
Kwan-Liu Ma University of California, Davis
Sameer Kumar
Sameer Kumar Google (United States)
John A. Gunnels
John A. Gunnels Nvidia (United States)
Robert Ross
Robert Ross Argonne National Laboratory
William Gropp
William Gropp University of Illinois at Urbana-Champaign

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