Abhinav Bhatele

ORCID

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 71

Top Venues

CoRR

IPDPS

IEEE Trans. Vis. Comput. Graph.

Publications

Onur Cankur, Aditya Tomar, Daniel Nichols, Connor Scully-Allison, Katherine E. Isaacs, Abhinav Bhatele
Automated Programmatic Performance Analysis of Parallel Programs. CoRR (2024)
Sean McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein
Transformers Can Do Arithmetic with the Right Embeddings. CoRR (2024)
Joy Kitson, Ian J. Costello, Jiangzhuo Chen, Diego Jiménez, Stefan Hoops, Henning S. Mortveit, Esteban Meneses, Jae-Seung Yeom, Madhav V. Marathe, Abhinav Bhatele
A Large-Scale Epidemic Simulation Framework for Realistic Social Contact Networks. CoRR (2024)
Daniel Nichols, Joshua Hoke Davis, Zhaojun Xie, Arjun Rajaram, Abhinav Bhatele
Can Large Language Models Write Parallel Code? CoRR (2024)
Vasu Singla, Kaiyu Yue, Sukriti Paul, Reza Shirkavand, Mayuka Jayawardhana, Alireza Ganjdanesh, Heng Huang, Abhinav Bhatele, Gowthami Somepalli, Tom Goldstein
From Pixels to Prose: A Large Dataset of Dense Image Captions. CoRR (2024)
Abhimanyu Hans, Yuxin Wen, Neel Jain, John Kirchenbauer, Hamid Kazemi, Prajwal Singhania, Siddharth Singh, Gowthami Somepalli, Jonas Geiping, Abhinav Bhatele, Tom Goldstein
Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs. CoRR (2024)
Harshitha Menon, Daniel Nichols, Abhinav Bhatele, Todd Gamblin
Learning to Predict and Improve Build Successes in Package Ecosystems. MSR (2024)
Daniel Nichols, Pranav Polasam, Harshitha Menon, Aniruddha Marathe, Todd Gamblin, Abhinav Bhatele
Performance-Aligned LLMs for Generating Fast Code. CoRR (2024)
Daniel Nichols, Alexander Movsesyan, Jae-Seung Yeom, Abhik Sarkar, Daniel Milroy, Tapasya Patki, Abhinav Bhatele
Predicting Cross-Architecture Performance of Parallel Programs. IPDPS (2024)
Connor Scully-Allison, Ian Lumsden, Katy Williams, Jesse Bartels, Michela Taufer, Stephanie Brink, Abhinav Bhatele, Olga Pearce, Katherine E. Isaacs
Design Concerns for Integrated Scripting and Interactive Visualization in Notebook Environments. IEEE Trans. Vis. Comput. Graph. 30 (9) (2024)
Harsh Khetawat, Nikhil Jain, Abhinav Bhatele, Frank Mueller
Predicting GPUDirect Benefits for HPC Workloads. PDP (2024)
Prajwal Singhania, Siddharth Singh, Shwai He, Soheil Feizi, Abhinav Bhatele
Loki: Low-Rank Keys for Efficient Sparse Attention. CoRR (2024)
Joshua Hoke Davis, Pranav Sivaraman, Isaac Minn, Konstantinos Parasyris, Harshitha Menon, Giorgis Georgakoudis, Abhinav Bhatele
An Evaluative Comparison of Performance Portability across GPU Programming Models. CoRR (2024)
Suraj P. Kesavan, Harsh Bhatia, Abhinav Bhatele, Stephanie Brink, Olga Pearce, Todd Gamblin, Peer-Timo Bremer, Kwan-Liu Ma
Scalable Comparative Visualization of Ensembles of Call Graphs. IEEE Trans. Vis. Comput. Graph. 29 (3) (2023)
Siddharth Singh, Olatunji Ruwase, Ammar Ahmad Awan, Samyam Rajbhandari, Yuxiong He, Abhinav Bhatele
A Hybrid Tensor-Expert-Data Parallelism Approach to Optimize Mixture-of-Experts Training. ICS (2023)
Yiheng Xu, Pranav Sivaraman, Hariharan Devarajan, Kathryn M. Mohror, Abhinav Bhatele
ML-based Modeling to Predict I/O Performance on Different Storage Sub-systems. CoRR (2023)
Siddharth Singh, Abhinav Bhatele
Exploiting Sparsity in Pruned Neural Networks to Optimize Large Model Training. CoRR (2023)
Joshua Hoke Davis, Justin Shafner, Daniel Nichols, Nathan Grube, Pino Martin, Abhinav Bhatele
Porting a Computational Fluid Dynamics Code with AMR to Large-scale GPU Platforms. IPDPS (2023)
Daniel Nichols, Aniruddha Marathe, Harshitha Menon, Todd Gamblin, Abhinav Bhatele
Modeling Parallel Programs using Large Language Models. CoRR (2023)
Siddharth Singh, Olatunji Ruwase, Ammar Ahmad Awan, Samyam Rajbhandari, Yuxiong He, Abhinav Bhatele
A Novel Tensor-Expert Hybrid Parallelism Approach to Scale Mixture-of-Experts Training. CoRR (2023)
Siddharth Singh, Zack Sating, Abhinav Bhatele
Communication-minimizing Asynchronous Tensor Parallelism. CoRR (2023)
Siddharth Singh, Abhinav Bhatele
Exploiting Sparsity in Pruned Neural Networks to Optimize Large Model Training. IPDPS (2023)
Siddharth Singh, Zachary Sating, Abhinav Bhatele
Jorge: Approximate Preconditioning for GPU-efficient Second-order Optimization. CoRR (2023)
Abhinav Bhatele, Rakrish Dhakal, Alexander Movsesyan, Aditya Ranjan, Jordan Marry, Onur Cankur
Pipit: Enabling programmatic analysis of parallel execution traces. CoRR (2023)
Siddharth Singh, Abhinav Bhatele
AxoNN: An asynchronous, message-driven parallel framework for extreme-scale deep learning. IPDPS (2022)
Onur Cankur, Abhinav Bhatele
Comparative Evaluation of Call Graph Generation by Profiling Tools. ISC (2022)
Daniel Nichols, Aniruddha Marathe, Kathleen Shoga, Todd Gamblin, Abhinav Bhatele
Resource Utilization Aware Job Scheduling to Mitigate Performance Variability. IPDPS (2022)
Connor Scully-Allison, Ian Lumsden, Katy Williams, Jesse Bartels, Michela Taufer, Stephanie Brink, Abhinav Bhatele, Olga Pearce, Katherine E. Isaacs
Designing an Interactive, Notebook-Embedded, Tree Visualization to Support Exploratory Performance Analysis. CoRR (2022)
Siddharth Singh, Abhinav Bhatele
Myelin: An asynchronous, message-driven parallel framework for extreme-scale deep learning. CoRR (2021)
Saptarshi Bhowmik, Nikhil Jain, Xin Yuan, Abhinav Bhatele
A Simulation Study of Hardware Parameters for Future GPU-based HPC Platforms. IPCCC (2021)
Shu-Huai Lin, Daniel Nichols, Siddharth Singh, Abhinav Bhatele
How to Train Your Neural Network: A Comparative Evaluation. CoRR (2021)
Huu Tan Nguyen, Abhinav Bhatele, Nikhil Jain, Suraj P. Kesavan, Harsh Bhatia, Todd Gamblin, Kwan-Liu Ma, Peer-Timo Bremer
Visualizing Hierarchical Performance Profiles of Parallel Codes Using CallFlow. IEEE Trans. Vis. Comput. Graph. 27 (4) (2021)
Suraj P. Kesavan, Harsh Bhatia, Abhinav Bhatele, Todd Gamblin, Peer-Timo Bremer, Kwan-Liu Ma
Scalable Comparative Visualization of Ensembles of Call Graphs. CoRR (2020)
Stephanie Brink, Ian Lumsden, Connor Scully-Allison, Katy Williams, Olga Pearce, Todd Gamblin, Michela Taufer, Katherine E. Isaacs, Abhinav Bhatele
Usability and Performance Improvements in Hatchet. HUST/ProTools@SC (2020)
Jaemin Choi, David F. Richards, Laxmikant V. Kalé, Abhinav Bhatele
End-to-end performance modeling of distributed GPU applications. ICS (2020)
Abhinav Bhatele, Jayaraman J. Thiagarajan, Taylor Groves, Rushil Anirudh, Staci A. Smith, Brandon Cook, David K. Lowenthal
The Case of Performance Variability on Dragonfly-based Systems. IPDPS (2020)
Sascha Hunold, Abhinav Bhatele, George Bosilca, Peter Knees
Predicting MPI Collective Communication Performance Using Machine Learning. CLUSTER (2020)
Harshitha Menon, Abhinav Bhatele, Todd Gamblin
Auto-tuning Parameter Choices in HPC Applications using Bayesian Optimization. IPDPS (2020)
Ian J. Costello, Abhinav Bhatele
Analytics of Longitudinal System Monitoring Data for Performance Prediction. CoRR (2020)
Giorgis Georgakoudis, Nikhil Jain, Takatsugu Ono, Koji Inoue, Shinobu Miwa, Abhinav Bhatele
Evaluating the Impact of Energy Efficient Networks on HPC Workloads. HiPC (2019)
Abhinav Bhatele, Nikhil Jain, Misbah Mubarak, Todd Gamblin
Analyzing Cost-Performance Tradeoffs of HPC Network Designs under Different Constraints using Simulations. SIGSIM-PADS (2019)
Emilio Castillo, Nikhil Jain, Marc Casas, Miquel Moretó, Martin Schulz, Ramón Beivide, Mateo Valero, Abhinav Bhatele
Optimizing computation-communication overlap in asynchronous task-based programs: poster. PPoPP (2019)
Emilio Castillo, Nikhil Jain, Marc Casas, Miquel Moretó, Martin Schulz, Ramón Beivide, Mateo Valero, Abhinav Bhatele
Optimizing computation-communication overlap in asynchronous task-based programs. ICS (2019)
Abhinav Bhatele, Stephanie Brink, Todd Gamblin
Hatchet: pruning the overgrowth in parallel profiles. SC (2019)
Jayaraman J. Thiagarajan, Nikhil Jain, Rushil Anirudh, Alfredo Giménez, Rahul Sridhar, Aniruddha Marathe, Tao Wang, Murali Emani, Abhinav Bhatele, Todd Gamblin
Bootstrapping Parameter Space Exploration for Fast Tuning. ICS (2018)
Harsh Bhatia, Nikhil Jain, Abhinav Bhatele, Yarden Livnat, Jens Domke, Valerio Pascucci, Peer-Timo Bremer
Interactive Investigation of Traffic Congestion on Fat-Tree Networks Using TreeScope. Comput. Graph. Forum 37 (3) (2018)
Alfredo Giménez, Todd Gamblin, Ilir Jusufi, Abhinav Bhatele, Martin Schulz, Peer-Timo Bremer, Bernd Hamann
MemAxes: Visualization and Analytics for Characterizing Complex Memory Performance Behaviors. IEEE Trans. Vis. Comput. Graph. 24 (7) (2018)
Alexandre Bergel, Abhinav Bhatele, David Böhme, Patrick Gralka, Kevin Griffin, Marc-André Hermanns, Dusan Okanovic, Olga Pearce, Tom Vierjahn
Visual Analytics Challenges in Analyzing Calling Context Trees. ESPT/VPA@SC (2018)
Kevin A. Brown, Nikhil Jain, Satoshi Matsuoka, Martin Schulz, Abhinav Bhatele
Interference between I/O and MPI Traffic on Fat-tree Networks. ICPP (2018)
Samuel D. Pollard, Nikhil Jain, Stephen Herbein, Abhinav Bhatele
Evaluation of an interference-free node allocation policy on fat-tree clusters. SC (2018)
Jayaraman J. Thiagarajan, Rushil Anirudh, Bhavya Kailkhura, Nikhil Jain, Tanzima Z. Islam, Abhinav Bhatele, Jae-Seung Yeom, Todd Gamblin
PADDLE: Performance Analysis Using a Data-Driven Learning Environment. IPDPS (2018)
Staci A. Smith, Clara E. Cromey, David K. Lowenthal, Jens Domke, Nikhil Jain, Jayaraman J. Thiagarajan, Abhinav Bhatele
Mitigating inter-job interference using adaptive flow-aware routing. SC (2018)
Alfredo Giménez, Todd Gamblin, Abhinav Bhatele, Chad Wood, Kathleen Shoga, Aniruddha Marathe, Peer-Timo Bremer, Bernd Hamann, Martin Schulz
ScrubJay: deriving knowledge from the disarray of HPC performance data. SC (2017)
Misbah Mubarak, Nikhil Jain, Jens Domke, Noah Wolfe, Caitlin Ross, Jianping Kelvin Li, Abhinav Bhatele, Christopher D. Carothers, Kwan-Liu Ma, Robert B. Ross
Toward reliable validation of HPC network simulation models. WSC (2017)
Misbah Mubarak, Philip H. Carns, Jonathan Jenkins, Jianping Kelvin Li, Nikhil Jain, Shane Snyder, Robert B. Ross, Christopher D. Carothers, Abhinav Bhatele, Kwan-Liu Ma
Quantifying I/O and Communication Traffic Interference on Dragonfly Networks Equipped with Burst Buffers. CLUSTER (2017)
Kevin A. Brown, Tianqi Xu, Keita Iwabuchi, Kento Sato, Adam Moody, Kathryn Mohror, Nikhil Jain, Abhinav Bhatele, Martin Schulz, Roger A. Pearce, Maya B. Gokhale, Satoshi Matsuoka
Accelerating Big Data Infrastructure and Applications (Ongoing Collaboration). ICDCS Workshops (2017)
Nikhil Jain, Abhinav Bhatele, Louis H. Howell, David Böhme, Ian Karlin, Edgar A. León, Misbah Mubarak, Noah Wolfe, Todd Gamblin, Matthew L. Leininger
Predicting the performance impact of different fat-tree configurations. SC (2017)
Nikhil Jain, Abhinav Bhatele, Xiang Ni, Todd Gamblin, Laxmikant V. Kalé
Partitioning Low-Diameter Networks to Eliminate Inter-Job Interference. IPDPS (2017)
Aniruddha Marathe, Rushil Anirudh, Nikhil Jain, Abhinav Bhatele, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Jae-Seung Yeom, Barry Rountree, Todd Gamblin
Performance modeling under resource constraints using deep transfer learning. SC (2017)
Abhinav Bhatele, Jae-Seung Yeom, Nikhil Jain, Chris J. Kuhlman, Yarden Livnat, Keith R. Bisset, Laxmikant V. Kalé, Madhav V. Marathe
Massively Parallel Simulations of Spread of Infectious Diseases over Realistic Social Networks. CCGrid (2017)
Noah Wolfe, Misbah Mubarak, Nikhil Jain, Jens Domke, Abhinav Bhatele, Christopher D. Carothers, Robert B. Ross
Preliminary Performance Analysis of Multi-rail Fat-tree Networks. CCGrid (2017)
Erik W. Draeger, Xavier Andrade, John A. Gunnels, Abhinav Bhatele, Andre Schleife, Alfredo A. Correa
Massively parallel first-principles simulation of electron dynamics in materials. J. Parallel Distributed Comput. 106 (2017)
Erik W. Draeger, Xavier Andrade, John A. Gunnels, Abhinav Bhatele, Andre Schleife, Alfredo A. Correa
Massively Parallel First-Principles Simulation of Electron Dynamics in Materials. IPDPS (2016)
Huu Tan Nguyen, Lai Wei, Abhinav Bhatele, Todd Gamblin, David Böhme, Martin Schulz, Kwan-Liu Ma, Peer-Timo Bremer
VIPACT: A Visualization Interface for Analyzing Calling Context Trees. VPA@SC (2016)
Edgar A. León, Ian Karlin, Abhinav Bhatele, Steven H. Langer, Chris Chambreau, Louis H. Howell, Trent D'Hooge, Matthew L. Leininger
Characterizing parallel scientific applications on commodity clusters: an empirical study of a tapered fat-tree. SC (2016)
Tanzima Z. Islam, Jayaraman J. Thiagarajan, Abhinav Bhatele, Martin Schulz, Todd Gamblin
A machine learning framework for performance coverage analysis of proxy applications. SC (2016)
Abhinav Bhatele, Nikhil Jain, Yarden Livnat, Valerio Pascucci, Peer-Timo Bremer
Analyzing Network Health and Congestion in Dragonfly-Based Supercomputers. IPDPS (2016)
Katherine E. Isaacs, Todd Gamblin, Abhinav Bhatele, Martin Schulz, Bernd Hamann, Peer-Timo Bremer
Ordering Traces Logically to Identify Lateness in Message Passing Programs. IEEE Trans. Parallel Distributed Syst. 27 (3) (2016)
Aniruddha Marathe, Hormozd Gahvari, Jae-Seung Yeom, Abhinav Bhatele
LibPowerMon: A Lightweight Profiling Framework to Profile Program Context and System-Level Metrics. IPDPS Workshops (2016)
Nikhil Jain, Abhinav Bhatele, Sam White, Todd Gamblin, Laxmikant V. Kalé
Evaluating HPC networks via simulation of parallel workloads. SC (2016)
Jae-Seung Yeom, Jayaraman J. Thiagarajan, Abhinav Bhatele, Greg Bronevetsky, Tzanio V. Kolev
Data-Driven Performance Modeling of Linear Solvers for Sparse Matrices. PMBS@SC (2016)
Abhinav Bhatele, Andrew R. Titus, Jayaraman J. Thiagarajan, Nikhil Jain, Todd Gamblin, Peer-Timo Bremer, Martin Schulz, Laxmikant V. Kalé
Identifying the Culprits Behind Network Congestion. IPDPS (2015)
Nikhil Jain, Abhinav Bhatele, Jae-Seung Yeom, Mark F. Adams, Francesco Miniati, Chao Mei, Laxmikant V. Kalé
Charm++ and MPI: Combining the Best of Both Worlds. IPDPS (2015)
Bilge Acun, Nikhil Jain, Abhinav Bhatele, Misbah Mubarak, Christopher D. Carothers, Laxmikant V. Kalé
Preliminary Evaluation of a Parallel Trace Replay Tool for HPC Network Simulations. Euro-Par Workshops (2015)
Katherine E. Isaacs, Abhinav Bhatele, Jonathan Lifflander, David Böhme, Todd Gamblin, Martin Schulz, Bernd Hamann, Peer-Timo Bremer
Recovering logical structure from Charm++ event traces. SC (2015)
Jae-Seung Yeom, Abhinav Bhatele, Keith R. Bisset, Eric J. Bohm, Abhishek Gupta, Laxmikant V. Kalé, Madhav V. Marathe, Dimitrios S. Nikolopoulos, Martin Schulz, Lukasz Wesolowski
Overcoming the Scalability Challenges of Epidemic Simulations on Blue Waters. IPDPS (2014)
Abhinav Bhatele, Nikhil Jain, Katherine E. Isaacs, Ronak Buch, Todd Gamblin, Steven H. Langer, Laxmikant V. Kalé
Optimizing the performance of parallel applications on a 5D torus via task mapping. HiPC (2014)
Ahmed H. Abdel-Gawad, Mithuna Thottethodi, Abhinav Bhatele
RAHTM: Routing Algorithm Aware Hierarchical Task Mapping. SC (2014)
Katherine E. Isaacs, Todd Gamblin, Abhinav Bhatele, Peer-Timo Bremer, Martin Schulz, Bernd Hamann
Extracting logical structure and identifying stragglers in parallel execution traces. PPOPP (2014)
Nikhil Jain, Abhinav Bhatele, Xiang Ni, Nicholas J. Wright, Laxmikant V. Kalé
Maximizing Throughput on a Dragonfly Network. SC (2014)
Steven H. Langer, Abhinav Bhatele, Charles H. Still
pF3D Simulations of Laser-Plasma Interactions in National Ignition Facility Experiments. Comput. Sci. Eng. 16 (6) (2014)
Katherine E. Isaacs, Peer-Timo Bremer, Ilir Jusufi, Todd Gamblin, Abhinav Bhatele, Martin Schulz, Bernd Hamann
Combing the Communication Hairball: Visualizing Parallel Execution Traces using Logical Time. IEEE Trans. Vis. Comput. Graph. 20 (12) (2014)
Alfredo Giménez, Todd Gamblin, Barry Rountree, Abhinav Bhatele, Ilir Jusufi, Peer-Timo Bremer, Bernd Hamann
Dissecting On-Node Memory Access Performance: A Semantic Approach. SC (2014)
Collin M. McCarthy, Katherine E. Isaacs, Abhinav Bhatele, Peer-Timo Bremer, Bernd Hamann
Visualizing the five-dimensional torus network of the IBM blue gene/Q. VPA@SC (2014)
Katherine E. Isaacs, Alfredo Giménez, Ilir Jusufi, Todd Gamblin, Abhinav Bhatele, Martin Schulz, Bernd Hamann, Peer-Timo Bremer
State of the Art of Performance Visualization. EuroVis (STARs) (2014)
Nikhil Jain, Abhinav Bhatele, Michael P. Robson, Todd Gamblin, Laxmikant V. Kalé
Predicting application performance using supervised learning on communication features. SC (2013)
Martin Schulz, Jim Belak, Abhinav Bhatele, Peer-Timo Bremer, Greg Bronevetsky, Marc Casas, Todd Gamblin, Katherine E. Isaacs, Ignacio Laguna, Joshua A. Levine, Valerio Pascucci, David F. Richards, Barry Rountree
Performance Analysis Techniques for the Exascale Co-Design Process. PARCO (2013)
Ian Karlin, Abhinav Bhatele, Jeff Keasler, Bradford L. Chamberlain, Jonathan D. Cohen, Zachary DeVito, Riyaz Haque, Dan Laney, Edward Luke, Felix Wang, David F. Richards, Martin Schulz, Charles H. Still
Exploring Traditional and Emerging Parallel Programming Models Using a Proxy Application. IPDPS (2013)
Abhinav Bhatele, Kathryn Mohror, Steve H. Langer, Katherine E. Isaacs
There goes the neighborhood: performance degradation due to nearby jobs. SC (2013)
Aaditya G. Landge, Joshua A. Levine, Abhinav Bhatele, Katherine E. Isaacs, Todd Gamblin, Martin Schulz, Steve H. Langer, Peer-Timo Bremer, Valerio Pascucci
Visualizing Network Traffic to Understand the Performance of Massively Parallel Simulations. IEEE Trans. Vis. Comput. Graph. 18 (12) (2012)
Laércio Lima Pilla, Christiane Pousa Ribeiro, Daniel Cordeiro, Chao Mei, Abhinav Bhatele, Philippe Olivier Alexandre Navaux, François Broquedis, Jean-François Méhaut, Laxmikant V. Kalé
A Hierarchical Approach for Load Balancing on Parallel Multi-core Systems. ICPP (2012)
Abhinav Bhatele, Todd Gamblin, Katherine E. Isaacs, Brian T. N. Gunney, Martin Schulz, Peer-Timo Bremer, Bernd Hamann
Novel views of performance data to analyze large-scale adaptive applications. SC (2012)
Abhinav Bhatele, Todd Gamblin, Steve H. Langer, Peer-Timo Bremer, Erik W. Draeger, Bernd Hamann, Katherine E. Isaacs, Aaditya G. Landge, Joshua A. Levine, Valerio Pascucci, Martin Schulz, Charles H. Still
Mapping applications with collectives over sub-communicators on torus networks. SC (2012)
Martin Schulz, Abhinav Bhatele, Peer-Timo Bremer, Todd Gamblin, Katherine E. Isaacs, Joshua A. Levine, Valerio Pascucci
Creating a Tool Set for Optimizing Topology-Aware Node Mappings. Parallel Tools Workshop (2011)
Vivek Kale, Abhinav Bhatele, William D. Gropp
Weighted locality-sensitive scheduling for mitigating noise on multi-core clusters. HiPC (2011)
Abhinav Bhatele, Pritish Jetley, Hormozd Gahvari, Lukasz Wesolowski, William D. Gropp, Laxmikant V. Kalé
Architectural Constraints to Attain 1 Exaflop/s for Three Scientific Application Classes. IPDPS (2011)
Edgar Solomonik, Abhinav Bhatele, James Demmel
Improving communication performance in dense linear algebra via topology aware collectives. SC (2011)
Gengbin Zheng, Abhinav Bhatele, Esteban Meneses, Laxmikant V. Kalé
Periodic hierarchical load balancing for large supercomputers. Int. J. High Perform. Comput. Appl. 25 (4) (2011)
Ehsan Totoni, Abhinav Bhatele, Eric J. Bohm, Nikhil Jain, Celso L. Mendes, Ryan M. Mokos, Gengbin Zheng, Laxmikant V. Kalé
Simulation-Based Performance Analysis and Tuning for a Two-Level Directly Connected System. ICPADS (2011)
Abhinav Bhatele, Laxmikant V. Kalé
Heuristic-Based Techniques for Mapping Irregular Communication Graphs to Mesh Topologies. HPCC (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Abhinav Bhatele