Venkatram Vishwanath
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
82
Venues
23
Active years
2004–2026
Best venue rank
A*
Where they publish
- ASC42 papers
- CCLUSTER8 papers
- BCCGRID7 papers
- BEuroPar3 papers
- NationalHiPC2 papers
- AHPDC2 papers
- CEGPGV2 papers
- AEACL1 paper
- A*AAAI1 paper
- BICIP1 paper
- A*ICLR1 paper
- A*SIGMETRICS1 paper
- AUSENIX1 paper
- AICS1 paper
- A*SIGMOD1 paper
- CCAIP1 paper
- BICPP1 paper
- CPDP1 paper
- BPACT1 paper
- AMMSys1 paper
- CMEMOCODE1 paper
- CBroadnets1 paper
- BGLOBECOM1 paper
Papers
82 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | EACL | PagedEviction: Structured Block-wise KV Cache Pruning for Efficient Large Language Model Inference. | Krishna Teja Chitty-Venkata, Jie Ye, Siddhisanket Raskar, Anthony Kougkas, Xian-He Sun, Murali Emani, Venkatram Vishwanath, Bogdan Nicolae |
| 2025 | AAAI | A Deep Probabilistic Framework for Continuous Time Dynamic Graph Generation. | Ryien Hosseini, Filippo Simini, Venkatram Vishwanath, Henry Hoffmann |
| 2025 | CCGRID | Evaluating Energy Efficiency of Ai Accelerators Using Two Mlperf Benchmarks. | Farah Ferdaus, Xingfu Wu, Valerie Taylor, Zhiling Lan, Sanjif Shanmugavelu, Venkatram Vishwanath, Michael E. Papka |
| 2025 | HiPC | Machine Learning Driven Auto-Tuning for Non-Uniform All-to-All Collectives. | Kunting Qi, Ke Fan, Jens Domke, Seydou Ba, Venkatram Vishwanath, Michael E. Papka, Sidharth Kumar |
| 2025 | ICIP | Langvision-Lora-Nas: Neural Architecture Search for Variable Lora Rank In Vision Language Models. | Krishna Teja Chitty-Venkata, Murali Emani, Venkatram Vishwanath |
| 2025 | ICLR | Quality Measures for Dynamic Graph Generative Models. | Ryien Hosseini, Filippo Simini, Venkatram Vishwanath, Rebecca Willett, Henry Hoffmann |
| 2025 | SC | AskHPC: A ChatBot for High Performance Computing User Support. | Akhilesh Bondapalli, Huihuo Zheng, Oluwaseun T. Ajayi, Murat Keeli, Haritha Siddabathuni Som, J. Taylor Childers, Lisa Childers, Yasaman Ghadar, Michael E. Papka, Venkatram Vishwanath, Rong Ge |
| 2025 | SC | MoE-Inference-Bench: Performance Evaluation of Mixture of Expert Large Language and Vision Models. | Krishna Teja Chitty-Venkata, Sylvia Howland, Golara Azar, Daria Soboleva, Natalia Vassilieva, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath |
| 2025 | SC | AERIS: Argonne Earth Systems Model for Reliable and Skillful Predictions. | Vin Hatanp, Eugene Ku, Jason Stock, Murali Emani, Sam Foreman, Chunyong Jung, Sandeep Madireddy, Tung Nguyen, Varuni Sastry, Ray A. O. Sinurat, Huihuo Zheng, Sam Wheeler, Troy Arcomano, Venkatram Vishwanath, Rao Kotamarthi |
| 2025 | SC | FIRST: Federated Inference Resource Scheduling Toolkit for Scientific AI Model Access. | Aditya Tanikanti, Benot Ct, Yanfei Guo, Le Chen, Nicholaus Saint, Ryan Chard, Ken Raffenetti, Rajeev Thakur, Thomas D. Uram, Ian T. Foster, Michael E. Papka, Venkatram Vishwanath |
| 2024 | CCGRID | A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems. | Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma |
| 2024 | EuroPar | WActiGrad: Structured Pruning for Efficient Finetuning and Inference of Large Language Models on AI Accelerators. | Krishna Teja Chitty-Venkata, Varuni Katti Sastry, Murali Emani, Venkatram Vishwanath, Sanjif Shanmugavelu, Sylvia Howland |
| 2024 | SC | Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling. | Shivam Barwey, Riccardo Balin, Bethany Lusch, Saumil Patel, Ramesh Balakrishnan, Pinaki Pal, Romit Maulik, Venkatram Vishwanath |
| 2024 | SC | LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators. | Krishna Teja Chitty-Venkata, Siddhisanket Raskar, Bharat Kale, Farah Ferdaus, Aditya Tanikanti, Ken Raffenetti, Valerie Taylor, Murali Emani, Venkatram Vishwanath |
| 2024 | SC | MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows with Direct Preference Optimization. | Gautham Dharuman, Kyle Hippe, Alexander Brace, Sam Foreman, Vin Hatanp, Varuni K. Sastry, Huihuo Zheng, Logan T. Ward, Servesh Muralidharan, Archit Vasan, Bharat Kale, Carla M. Mann, Heng Ma, Yun-Hsuan Cheng, Yuliana Zamora, Shengchao Liu, Chaowei Xiao, Murali Emani, Tom Gibbs, Mahidhar Tatineni, Deepak Canchi, Jerome Mitchell, Koichi Yamada, Maria Garzaran, Michael E. Papka, Ian T. Foster, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan |
| 2024 | SC | An Incremental Multi-Level, Multi-Scale Approach to Assessment of Multifidelity HPC Systems. | Shilpika, Bethany Lusch, Venkatram Vishwanath, Michael E. Papka |
| 2024 | SIGMETRICS | Thorough Characterization and Analysis of Large Transformer Model Training At-Scale. | Scott Cheng, Jun-Liang Lin, Murali Emani, Siddhisanket Raskar, Sam Foreman, Zhen Xie, Venkatram Vishwanath, Mahmut T. Kandemir |
| 2024 | USENIX | Centimani: Enabling Fast AI Accelerator Selection for DNN Training with a Novel Performance Predictor. | Zhen Xie, Murali Emani, Xiaodong Yu, Dingwen Tao, Xin He, Pengfei Su, Keren Zhou, Venkatram Vishwanath |
| 2023 | EuroPar | TrainBF: High-Performance DNN Training Engine Using BFloat16 on AI Accelerators. | Zhen Xie, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath |
| 2023 | SC | Characterizing the Performance of Triangle Counting on Graphcore's IPU Architecture. | Reet Barik, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath |
| 2023 | SC | Demonstration of Portable Performance of Scientific Machine Learning on High Performance Computing Systems. | Khalid Hossain, Riccardo Balin, Corey Adams, Thomas D. Uram, Kalyan Kumaran, Venkatram Vishwanath, Tanima Dey, Subrata Goswami, Janghaeng Lee, Rebecca Ramer, Koichi Yamada |
| 2023 | SC | Scalable Lead Prediction with Transformers using HPC resources. | Archit Vasan, Thomas S. Brettin, Rick Stevens, Arvind Ramanathan, Venkatram Vishwanath |
| 2022 | CCGRID | Stimulus: Accelerate Data Management for Scientific AI applications in HPC. | Hariharan Devarajan, Anthony Kougkas, Huihuo Zheng, Venkatram Vishwanath, Xian-He Sun |
| 2022 | CCGRID | Toward an In-Depth Analysis of Multifidelity High Performance Computing Systems. | Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma |
| 2022 | CCGRID | HDF5 Cache VOL: Efficient and Scalable Parallel I/O through Caching Data on Node-local Storage. | Huihuo Zheng, Venkatram Vishwanath, Quincey Koziol, Houjun Tang, John Ravi, John Mainzer, Suren Byna |
| 2022 | HPDC | Efficient Design Space Exploration for Sparse Mixed Precision Neural Architectures. | Krishna Teja Chitty-Venkata, Murali Emani, Venkatram Vishwanath, Arun K. Somani |
| 2021 | CCGRID | DLIO: A Data-Centric Benchmark for Scientific Deep Learning Applications. | Hariharan Devarajan, Huihuo Zheng, Anthony Kougkas, Xian-He Sun, Venkatram Vishwanath |
| 2021 | SC | AgEBO-tabular: joint neural architecture and hyperparameter search with autotuned data-parallel training for tabular data. | Romain gel, Prasanna Balaprakash, Isabelle Guyon, Venkatram Vishwanath, Fangfang Xia, Rick Stevens, Zhengying Liu |
| 2019 | SC | Scalable reinforcement-learning-based neural architecture search for cancer deep learning research. | Prasanna Balaprakash, Romain Egele, Misha Salim, Stefan M. Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens |
| 2019 | SC | Scaling Distributed Training of Flood-Filling Networks on HPC Infrastructure for Brain Mapping. | Wushi Dong, Nicola J. Ferrier, Narayanan Kasthuri, Peter Littlewood, Murat Keeli, Rafael Vescovi, Hanyu Li, Corey Adams, Elise Jennings, Samuel Flender, Thomas D. Uram, Venkatram Vishwanath |
| 2019 | SC | Balsam: Near Real-Time Experimental Data Analysis on Supercomputers. | Michael A. Salim, Thomas D. Uram, J. Taylor Childers, Venkatram Vishwanath, Michael E. Papka |
| 2019 | SC | MELA: A Visual Analytics Tool for Studying Multifidelity HPC System Logs. | Shilpika, Bethany Lusch, Murali Emani, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma |
| 2018 | CCGRID | Toward Scalable and Asynchronous Object-Centric Data Management for HPC. | Houjun Tang, Suren Byna, Francois Tessier, Teng Wang, Bin Dong, Jingqing Mu, Quincey Koziol, Jrome Soumagne, Venkatram Vishwanath, Jialin Liu, Richard Warren |
| 2018 | ICS | Optimizing Data Aggregation by Leveraging the Deep Memory Hierarchy on Large-scale Systems. | Franois Tessier, Paul Gressier, Venkatram Vishwanath |
| 2018 | SC | Benchmarking Machine Learning Methods for Performance Modeling of Scientific Applications. | Preeti Malakar, Prasanna Balaprakash, Venkatram Vishwanath, Vitali A. Morozov, Kalyan Kumaran |
| 2018 | SC | Topology-aware space-shared co-analysis of large-scale molecular dynamics simulations. | Preeti Malakar, Todd S. Munson, Christopher Knight, Venkatram Vishwanath, Michael E. Papka |
| 2018 | SC | libIS: a lightweight library for flexible in transit visualization. | Will Usher, Silvio Rizzi, Ingo Wald, Jefferson Amstutz, Joseph A. Insley, Venkatram Vishwanath, Nicola J. Ferrier, Michael E. Papka, Valerio Pascucci |
| 2017 | CLUSTER | TAPIOCA: An I/O Library for Optimized Topology-Aware Data Aggregation on Large-Scale Supercomputers. | Francois Tessier, Venkatram Vishwanath, Emmanuel Jeannot |
| 2017 | SC | Scalable In situ Analysis of Molecular Dynamics Simulations. | Preeti Malakar, Christopher Knight, Todd S. Munson, Venkatram Vishwanath, Michael E. Papka |
| 2017 | SC | PoLiMEr: An Energy Monitoring and Power Limiting Interface for HPC Applications. | Ivana Marincic, Venkatram Vishwanath, Henry Hoffmann |
| 2017 | SIGMOD | A distributed graph approach for pre-processing linked RDF data using supercomputers. | Michael J. Lewis, George K. Thiruvathukal, Venkatram Vishwanath, Michael E. Papka, Andrew E. Johnson |
| 2016 | SC | Performance analysis, design considerations, and applications of extreme-scale | Utkarsh Ayachit, Andrew C. Bauer, Earl P. N. Duque, Greg Eisenhauer, Nicola J. Ferrier, Junmin Gu, Kenneth E. Jansen, Burlen Loring, Zarija Lukic, Suresh Menon, Dmitriy Morozov, Patrick O'Leary, Reetesh Ranjan, Michel E. Rasquin, Christopher P. Stone, Venkatram Vishwanath, Gunther H. Weber, Brad Whitlock, Matthew Wolf, K. John Wu, E. Wes Bethel |
| 2016 | SC | Optimal execution of co-analysis for large-scale molecular dynamics simulations. | Preeti Malakar, Venkatram Vishwanath, Christopher Knight, Todd S. Munson, Michael E. Papka |
| 2016 | SC | Topology-Aware Data Aggregation for Intensive I/O on Large-Scale Supercomputers. | Francois Tessier, Preeti Malakar, Venkatram Vishwanath, Emmanuel Jeannot, Florin Isaila |
| 2016 | SC | A data driven scheduling approach for power management on HPC systems. | Sean Wallace, Xu Yang, Venkatram Vishwanath, William E. Allcock, Susan Coghlan, Michael E. Papka, Zhiling Lan |
| 2016 | SC | Early Investigations into Using a Remote RAM Pool with the vl3 Visualization Framework. | Dawid Zawislak, Brian R. Toonen, William E. Allcock, Silvio Rizzi, Joseph A. Insley, Venkatram Vishwanath, Michael E. Papka |
| 2015 | CAIP | TECA: Petascale Pattern Recognition for Climate Science. | Prabhat, Surendra Byna, Venkatram Vishwanath, Eli Dart, Michael F. Wehner, William D. Collins |
| 2015 | CLUSTER | Multipath Load Balancing for M N Communication Patterns on the Blue Gene/Q Supercomputer Interconnection Network. | Huy Bui, Robert L. Jacob, Preeti Malakar, Venkatram Vishwanath, Andrew E. Johnson, Michael E. Papka, Jason Leigh |
| 2015 | CLUSTER | Comparison of Vendor Supplied Environmental Data Collection Mechanisms. | Sean Wallace, Venkatram Vishwanath, Susan Coghlan, Zhiling Lan, Michael E. Papka |
| 2015 | EGPGV | Large-Scale Parallel Visualization of Particle-Based Simulations using Point Sprites and Level-Of-Detail. | Silvio Rizzi, Mark Hereld, Joseph A. Insley, Michael E. Papka, Thomas D. Uram, Venkatram Vishwanath |
| 2015 | HiPC | Improving Communication Throughput by Multipath Load Balancing on Blue Gene/Q. | Huy Bui, Preeti Malakar, Venkatram Vishwanath, Todd S. Munson, Eun-Sung Jung, Andrew E. Johnson, Michael E. Papka, Jason Leigh |
| 2015 | SC | Route-aware independent MPI I/O on the blue gene/Q. | Preeti Malakar, Venkatram Vishwanath |
| 2015 | SC | Optimal scheduling of in-situ analysis for large-scale scientific simulations. | Preeti Malakar, Venkatram Vishwanath, Todd S. Munson, Christopher Knight, Mark Hereld, Sven Leyffer, Michael E. Papka |
| 2014 | EGPGV | Performance Modeling of vl3 Volume Rendering on GPU-Based Clusters. | Silvio Rizzi, Mark Hereld, Joseph A. Insley, Michael E. Papka, Thomas D. Uram, Venkatram Vishwanath |
| 2014 | ICPP | Improving Multisite Workflow Performance Using Model-Based Scheduling. | Ketan Maheshwari, Eun-Sung Jung, Jiayuan Meng, Venkatram Vishwanath, Rajkumar Kettimuthu |
| 2014 | PDP | Scalable Parallel I/O on a Blue Gene/Q Supercomputer Using Compression, Topology-Aware Data Aggregation, and Subfiling. | Huy Bui, Hal Finkel, Venkatram Vishwanath, Salman Habib, Katrin Heitmann, Jason Leigh, Michael E. Papka, Kevin Harms |
| 2014 | SC | Distributed multipath routing algorithm for data center networks. | Eun-Sung Jung, Venkatram Vishwanath, Rajkumar Kettimuthu |
| 2014 | SC | Efficient I/O and Storage of Adaptive-Resolution Data. | Sidharth Kumar, John Edwards, Peer-Timo Bremer, Aaron Knoll, Cameron Christensen, Venkatram Vishwanath, Philip H. Carns, John A. Schmidt, Valerio Pascucci |
| 2013 | CLUSTER | Model-driven multisite workflow scheduling. | Ketan Maheshwari, Eun-Sung Jung, Jiayuan Meng, Venkatram Vishwanath, Rajkumar Kettimuthu |
| 2013 | CLUSTER | Application power profiling on IBM Blue Gene/Q. | Sean Wallace, Venkatram Vishwanath, Susan Coghlan, John R. Tramm, Zhiling Lan, Michael E. Papka |
| 2013 | EuroPar | A Generic High-Performance Method for Deinterleaving Scientific Data. | Eric R. Schendel, Steve Harenberg, Houjun Tang, Venkatram Vishwanath, Michael E. Papka, Nagiza F. Samatova |
| 2013 | HPDC | Scalable in situ scientific data encoding for analytical query processing. | Sriram Lakshminarasimhan, David A. Boyuka II, Saurabh V. Pendse, Xiaocheng Zou, John Jenkins, Venkatram Vishwanath, Michael E. Papka, Nagiza F. Samatova |
| 2013 | PACT | Characterization and Understanding Machine-Specific Interconnects. | Vitali A. Morozov, Jiayuan Meng, Venkatram Vishwanath, Kalyan Kumaran, Michael E. Papka |
| 2013 | SC | Characterization and modeling of PIDX parallel I/O for performance optimization. | Sidharth Kumar, Avishek Saha, Venkatram Vishwanath, Philip H. Carns, John A. Schmidt, Giorgio Scorzelli, Hemanth Kolla, Ray W. Grout, Robert Latham, Robert B. Ross, Michael E. Papka, Jacqueline Chen, Valerio Pascucci |
| 2013 | SC | On-demand unstructured mesh translation for reducing memory pressure during in situ analysis. | Jonathan Woodring, James P. Ahrens, Timothy J. Tautges, Tom Peterka, Venkatram Vishwanath, Berk Geveci |
| 2012 | CLUSTER | Evaluating Power-Monitoring Capabilities on IBM Blue Gene/P and Blue Gene/Q. | Kazutomo Yoshii, Kamil Iskra, Rinku Gupta, Peter H. Beckman, Venkatram Vishwanath, Chenjie Yu, Susan Coghlan |
| 2012 | SC | Abstract: Evaluating Communication Performance in BlueGene/Q and Cray XE6 Supercomputers. | Huy Bui, Venkatram Vishwanath, Jason Leigh, Michael E. Papka |
| 2012 | SC | Poster: Evaluating Communication Performance in BlueGene/Q and Cray XE6 Supercomputers. | Huy Bui, Venkatram Vishwanath, Jason Leigh, Michael E. Papka |
| 2012 | SC | Efficient data restructuring and aggregation for I/O acceleration in PIDX. | Sidharth Kumar, Venkatram Vishwanath, Philip H. Carns, Joshua A. Levine, Robert Latham, Giorgio Scorzelli, Hemanth Kolla, Ray W. Grout, Robert B. Ross, Michael E. Papka, Jacqueline Chen, Valerio Pascucci |
| 2012 | SC | Dataflow-driven GPU performance projection for multi-kernel transformations. | Jiayuan Meng, Vitali A. Morozov, Venkatram Vishwanath, Kalyan Kumaran |
| 2012 | SC | Accelerating Data Movement Leveraging End-System and Network Parallelism. | Jun Yi, Rajkumar Kettimuthu, Venkatram Vishwanath |
| 2011 | CLUSTER | PIDX: Efficient Parallel I/O for Multi-resolution Multi-dimensional Scientific Datasets. | Sidharth Kumar, Venkatram Vishwanath, Philip H. Carns, Brian Summa, Giorgio Scorzelli, Valerio Pascucci, Robert B. Ross, Jacqueline Chen, Hemanth Kolla, Ray W. Grout |
| 2011 | SC | Modeling early galaxies using radiation hydrodynamics. | Joseph A. Insley, Rick Wagner, Robert Harkness, Daniel R. Reynolds, Michael L. Norman, Mark Hereld, Eric C. Olson, Michael E. Papka, Venkatram Vishwanath |
| 2011 | SC | GROPHECY: GPU performance projection from CPU code skeletons. | Jiayuan Meng, Vitali A. Morozov, Kalyan Kumaran, Venkatram Vishwanath, Thomas D. Uram |
| 2011 | SC | Electronic poster: co-visualization of full data and in situ data extracts from unstructured grid cfd at 160k cores. | Michel E. Rasquin, Patrick Marion, Venkatram Vishwanath, Benjamin A. Matthews, Mark Hereld, Kenneth E. Jansen, Raymond M. Loy, Andrew C. Bauer, Min Zhou, Onkar Sahni, Jing Fu, Ning Liu, Christopher D. Carothers, Mark S. Shephard, Michael E. Papka, Kalyan Kumaran, Berk Geveci |
| 2011 | SC | Topology-aware data movement and staging for I/O acceleration on Blue Gene/P supercomputing systems. | Venkatram Vishwanath, Mark Hereld, Vitali A. Morozov, Michael E. Papka |
| 2010 | MMSys | Multi-application inter-tile synchronization on ultra-high-resolution display walls. | Sungwon Nam, Sachin Deshpande, Venkatram Vishwanath, Byungil Jeong, Luc Renambot, Jason Leigh |
| 2010 | SC | Accelerating I/O Forwarding in IBM Blue Gene/P Systems. | Venkatram Vishwanath, Mark Hereld, Kamil Iskra, Dries Kimpe, Vitali A. Morozov, Michael E. Papka, Robert B. Ross, Kazutomo Yoshii |
| 2008 | MEMOCODE | Specification and Verification of LambdaRAM: A Wide-area Distributed Cache for High Performance Computing. | Venkatram Vishwanath, Lenore D. Zuck, Jason Leigh |
| 2006 | Broadnets | LambdaBridge: A Scalable Architecture for Future Generation Terabit Applications. | Xi Wang, Venkatram Vishwanath, Byungil Jeong, Ratko Jagodic, Eric He, Luc Renambot, Andrew E. Johnson, Jason Leigh |
| 2006 | GLOBECOM | AR-PIN/PDC: Flexible Advance Reservation of Intradomain and Interdomain Lightpaths. | Eric He, Xi Wang, Venkatram Vishwanath, Jason Leigh |
| 2004 | CLUSTER | JuxtaView - a tool for interactive visualization of large imagery on scalable tiled displays. | Naveen K. Krishnaprasad, Venkatram Vishwanath, Shalini Venkataraman, A. G. Rao, Luc Renambot, Jason Leigh, Andrew E. Johnson, Brian Davis |