Venkatram Vishwanath

182 papers A* 2A 23B 10C 12Misc 3Journal 65Unranked 64

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Extending μP: Spectral Conditions for Feature Learning Across Optimizers. CoRR Akshita Gupta, Marieme Ngom, Sam Foreman, Venkatram Vishwanath
2026	—	`conf`	PagedEviction: Structured Block-wise KV Cache Pruning for Efficient Large Language Model Inference. EACL (Findings) Krishna Teja Chitty-Venkata, Jie Ye, Siddhisanket Raskar, Anthony Kougkas, Xian-He Sun, Murali Emani, Venkatram Vishwanath, Bogdan Nicolae
2026	J	`jnl`	Queue wait time prediction in high performance computing (HPC) systems. J. Supercomput. Nwamaka Okafor, Bethany Lusch, Venkatram Vishwanath
2026	J	`jnl`	Swimba: Switch Mamba Model Scales State Space Models. CoRR Zhixu Du, Krishna Teja Chitty-Venkata, Murali Emani, Venkatram Vishwanath, Hai Helen Li, Yiran Chen
2025	A*	`conf`	A Deep Probabilistic Framework for Continuous Time Dynamic Graph Generation. AAAI Ryien Hosseini, Filippo Simini, Venkatram Vishwanath, Henry Hoffmann
2025	A	`conf`	AERIS: Argonne Earth Systems Model for Reliable and Skillful Predictions. SC Väinö Hatanpää, 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	J	`jnl`	AERIS: Argonne Earth Systems Model for Reliable and Skillful Predictions. CoRR Väinö Hatanpää, Eugene Ku, Jason Stock, Murali Emani, Sam Foreman, Chunyong Jung, Sandeep Madireddy, Tung Nguyen, Varuni Katti Sastry, Ray A. O. Sinurat, Sam Wheeler, Huihuo Zheng, Troy Arcomano, Venkatram Vishwanath, Rao Kotamarthi
2025	—	`conf`	AI Assistants to Enhance and Exploit the PETSc Knowledge Base. ICPP Workshops Barry Smith, Junchao Zhang, Hong Zhang, Lois Curfman McInnes, Murat Keçeli, Archit Vasan, Satish Balay, Toby Isaac, Le Chen, Venkatram Vishwanath
2025	J	`jnl`	AI Assistants to Enhance and Exploit the PETSc Knowledge Base. CoRR Barry Smith, Junchao Zhang, Hong Zhang, Lois Curfman McInnes, Murat Keçeli, Archit Vasan, Satish Balay, Toby Isaac, Le Chen, Venkatram Vishwanath
2025	—	`conf`	AdaParse: An Adaptive Parallel PDF Parsing and Resource Scaling Engine. MLSys Carlo Siebenschuh, Kyle Hippe, Ozan Gökdemir, Alexander Brace, Arham Mushtaq Khan, Khalid Hossain, Yadu N. Babuji, Nicholas Chia, Venkatram Vishwanath, Arvind Ramanathan, Rick L. Stevens, Ian T. Foster, Robert Underwood
2025	J	`jnl`	AdaParse: An Adaptive Parallel PDF Parsing and Resource Scaling Engine. CoRR Carlo Siebenschuh, Kyle Hippe, Ozan Gökdemir, Alexander Brace, Arham Khan, Khalid Hossain, Yadu N. Babuji, Nicholas Chia, Venkatram Vishwanath, Rick Stevens, Arvind Ramanathan, Ian T. Foster, Robert Underwood
2025	J	`jnl`	An Incremental Multi-Level, Multi-Scale Approach to Assessment of Multifidelity HPC Systems. CoRR Shilpika, Bethany Lusch, Venkatram Vishwanath, Michael E. Papka
2025	—	`conf`	AskHPC: A ChatBot for High Performance Computing User Support. SC Workshops Akhilesh Bondapalli, Huihuo Zheng, Oluwaseun T. Ajayi, Murat Keçeli, Haritha Siddabathuni Som, J. Taylor Childers, Lisa Childers, Yasaman Ghadar, Michael E. Papka, Venkatram Vishwanath, Rong Ge
2025	J	`jnl`	Aurora: Architecting Argonne's First Exascale Supercomputer for Accelerated Scientific Discovery. CoRR Benjamin S. Allen, James L. Anchell, Victor Anisimov, Thomas Applencourt, Abhishek Bagusetty, Ramesh Balakrishnan, Riccardo Balin, Solomon Bekele, Colleen Bertoni, Cyrus Blackworth, Renzo Bustamante, Kevin Canada, John Carrier, Christopher Chan-nui, Lance C. Cheney, J. Taylor Childers, Paul K. Coffman, Susan Coghlan, Michael D'Mello, Murali Emani, Kyle Felker, Sam Foreman, Olivier Franza, Longfei Gao, Marta García, María Jesús Garzarán, Balazs Gerofi, Yasaman Ghadar, Neha Gupta, Kevin Harms, Väinö Hatanpää, Brian Holland, Carissa Holohan, Brian Homerding, Khalid Hossain, Louise Huot, Huda Ibeid, Joseph A. Insley, Sai Jayanthi, Hong Jiang, Wei Jiang, Xiao-Yong Jin, Jeongnim Kim, Christopher Knight, Kalyan Kumaran, JaeHyuk Kwack, Ti Leggett, Ben Lenard, Chris Lewis, Nevin Liber, Johann Lombardi, Raymond M. Loy, Ye Luo, Bethany Lusch, Nilakantan Mahadevan, Victor A. Mateevitsi, Gordon McPheeters, Ryan Milner, Vitali A. Morozov, Servesh Muralidharan, Tom Musta, Mrigendra Nagar, Vikram Narayana, Marieme Ngom, Anthony-Trung Nguyen, Nathan Nichols, Aditya Nishtala, James C. Osborn, Michael E. Papka, Scott Parker, Saumil Patel, Adrian C. Pope, Sucheta Raghunanda, Esteban Rangel, Paul M. Rich, Silvio Rizzi, Kris Rowe, Varuni Sastry, Adam Scovel, Filippo Simini, Haritha Siddabathuni Som, Patrick Steinbrecher, Rick Stevens, Xinmin Tian, Peter Upton, Thomas D. Uram, Archit Vasan, Álvaro Vázquez-Mayagoitia, Kaushik Velusamy, Brice Videau, Venkatram Vishwanath, Brian Whitney, Timothy J. Williams, Michael Woodacre, Sam Zeltner, Gengbin Zheng, Huihuo Zheng
2025	J	`jnl`	BaKlaVa - Budgeted Allocation of KV cache for Long-context Inference. CoRR Ahmed Burak Gulhan, Krishna Teja Chitty-Venkata, Murali Emani, Mahmut T. Kandemir, Venkatram Vishwanath
2025	—	`conf`	FIRST: Federated Inference Resource Scheduling Toolkit for Scientific AI Model Access. SC Workshops Aditya Tanikanti, Benoît Côté, Yanfei Guo, Le Chen, Nicholaus Saint, Ryan Chard, Ken Raffenetti, Rajeev Thakur, Thomas D. Uram, Ian T. Foster, Michael E. Papka, Venkatram Vishwanath
2025	J	`jnl`	FIRST: Federated Inference Resource Scheduling Toolkit for Scientific AI Model Access. CoRR Aditya Tanikanti, Benoît Côté, Yanfei Guo, Le Chen, Nicholaus Saint, Ryan Chard, Ken Raffenetti, Rajeev Thakur, Thomas D. Uram, Ian T. Foster, Michael E. Papka, Venkatram Vishwanath
2025	J	`jnl`	Foundation Models for Discovery and Exploration in Chemical Space. CoRR Alexius Wadell, Anoushka Bhutani, Victor Azumah, Austin R. Ellis-Mohr, Celia Kelly, Hancheng Zhao, Anuj K. Nayak, Kareem Hegazy, Alexander Brace, Hongyi Lin, Murali Emani, Venkatram Vishwanath, Kevin Gering, Melisa Alkan, Tom Gibbs, Jack C. Wells, Lav R. Varshney, Bharath Ramsundar, Karthik Duraisamy, Michael W. Mahoney, Arvind Ramanathan, Venkatasubramanian Viswanathan
2025	—	`conf`	HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights. PASC Ozan Gökdemir, Carlo Siebenschuh, Alexander Brace, Azton Wells, Brian Hsu, Kyle Hippe, Priyanka Setty, Aswathy Ajith, J. Gregory Pauloski, Varuni Sastry, Sam Foreman, Huihuo Zheng, Heng Ma, Bharat Kale, Nicholas Chia, Thomas Gibbs, Michael E. Papka, Thomas S. Brettin, Francis J. Alexander, Anima Anandkumar, Ian T. Foster, Rick Stevens, Venkatram Vishwanath, Arvind Ramanathan
2025	J	`jnl`	HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights. CoRR Ozan Gökdemir, Carlo Siebenschuh, Alexander Brace, Azton Wells, Brian Hsu, Kyle Hippe, Priyanka Vasanthakumari, Aswathy Ajith, J. Gregory Pauloski, Varuni Katti Sastry, Sam Foreman, Huihuo Zheng, Heng Ma, Bharat Kale, Nicholas Chia, Thomas Gibbs, Michael E. Papka, Thomas S. Brettin, Francis J. Alexander, Anima Anandkumar, Ian T. Foster, Rick Stevens, Venkatram Vishwanath, Arvind Ramanathan
2025	J	`jnl`	LExI: Layer-Adaptive Active Experts for Efficient MoE Model Inference. CoRR Krishna Teja Chitty-Venkata, Sandeep Madireddy, Murali Emani, Venkatram Vishwanath
2025	J	`jnl`	LangVision-LoRA-NAS: Neural Architecture Search for Variable LoRA Rank in Vision Language Models. CoRR Krishna Teja Chitty-Venkata, Murali Emani, Venkatram Vishwanath
2025	Misc	`conf`	Machine Learning Driven Auto-Tuning for Non-Uniform All-to-All Collectives. HiPC Kunting Qi, Ke Fan, Jens Domke, Seydou Ba, Venkatram Vishwanath, Michael E. Papka, Sidharth Kumar
2025	—	`conf`	MoE-Inference-Bench: Performance Evaluation of Mixture of Expert Large Language and Vision Models. SC Workshops Krishna Teja Chitty-Venkata, Sylvia Howland, Golara Azar, Daria Soboleva, Natalia Vassilieva, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath
2025	J	`jnl`	MoE-Inference-Bench: Performance Evaluation of Mixture of Expert Large Language and Vision Models. CoRR Krishna Teja Chitty-Venkata, Sylvia Howland, Golara Azar, Daria Soboleva, Natalia Vassilieva, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath
2025	J	`jnl`	PagedEviction: Structured Block-wise KV Cache Pruning for Efficient Large Language Model Inference. CoRR Krishna Teja Chitty-Venkata, Jie Ye, Xian-He Sun, Anthony Kougkas, Murali Emani, Venkatram Vishwanath, Bogdan Nicolae
2025	J	`jnl`	PreLoRA: Hybrid Pre-training of Vision Transformers with Full Training and Low-Rank Adapters. CoRR Krishu K. Thapa, Reet Barik, Krishna Teja Chitty-Venkata, Murali Emani, Venkatram Vishwanath
2025	A*	`conf`	Quality Measures for Dynamic Graph Generative Models. ICLR Ryien Hosseini, Filippo Simini, Venkatram Vishwanath, Rebecca Willett, Henry Hoffmann
2025	J	`jnl`	Quality Measures for Dynamic Graph Generative Models. CoRR Ryien Hosseini, Filippo Simini, Venkatram Vishwanath, Rebecca Willett, Henry Hoffmann
2025	J	`jnl`	Scalable Agentic Reasoning for Designing Biologics Targeting Intrinsically Disordered Proteins. CoRR Matthew Sinclair, Moeen Meigooni, Archit Vasan, Ozan Gökdemir, Xinran Lian, Heng Ma, Yadu N. Babuji, Alexander Brace, Khalid Hossain, Carlo Siebenschuh, Thomas S. Brettin, Kyle Chard, Christopher S. Henry, Venkatram Vishwanath, Rick L. Stevens, Ian T. Foster, Arvind Ramanathan
2025	J	`jnl`	Sketch-Augmented Features Improve Learning Long-Range Dependencies in Graph Neural Networks. CoRR Ryien Hosseini, Filippo Simini, Venkatram Vishwanath, Rebecca Willett, Henry Hoffmann
2024	J	`jnl`	A Deep Probabilistic Framework for Continuous Time Dynamic Graph Generation. CoRR Ryien Hosseini, Filippo Simini, Venkatram Vishwanath, Henry Hoffmann
2024	B	`conf`	A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems. CCGrid Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma
2024	J	`jnl`	Adding topology and memory awareness in data aggregation algorithms. Future Gener. Comput. Syst. François Tessier, Venkatram Vishwanath, Emmanuel Jeannot
2024	—	`conf`	An Incremental Multi-Level, Multi-Scale Approach to Assessment of Multifidelity HPC Systems. SC Workshops Shilpika, Bethany Lusch, Venkatram Vishwanath, Michael E. Papka
2024	—	`conf`	Centimani: Enabling Fast AI Accelerator Selection for DNN Training with a Novel Performance Predictor. USENIX ATC Zhen Xie, Murali Emani, Xiaodong Yu, Dingwen Tao, Xin He, Pengfei Su, Keren Zhou, Venkatram Vishwanath
2024	—	`conf`	High Performance Binding Affinity Prediction with a Transformer-Based Surrogate Model. IPDPS (Workshops) Archit Vasan, Ozan Gökdemir, Alexander Brace, Arvind Ramanathan, Thomas S. Brettin, Rick Stevens, Venkatram Vishwanath
2024	—	`conf`	LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators. SC Workshops Krishna Teja Chitty-Venkata, Siddhisanket Raskar, Bharat Kale, Farah Ferdaus, Aditya Tanikanti, Ken Raffenetti, Valerie Taylor, Murali Emani, Venkatram Vishwanath
2024	J	`jnl`	LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators. CoRR Krishna Teja Chitty-Venkata, Siddhisanket Raskar, Bharat Kale, Farah Ferdaus, Aditya Tanikanti, Ken Raffenetti, Valerie Taylor, Murali Emani, Venkatram Vishwanath
2024	A	`conf`	MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows with Direct Preference Optimization. SC Gautham Dharuman, Kyle Hippe, Alexander Brace, Sam Foreman, Väinö Hatanpää, Varuni Katti 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	J	`jnl`	Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks. CoRR Shivam Barwey, Pinaki Pal, Saumil Patel, Riccardo Balin, Bethany Lusch, Venkatram Vishwanath, Romit Maulik, Ramesh Balakrishnan
2024	—	`conf`	Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling. SC Workshops Shivam Barwey, Riccardo Balin, Bethany Lusch, Saumil Patel, Ramesh Balakrishnan, Pinaki Pal, Romit Maulik, Venkatram Vishwanath
2024	J	`jnl`	Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling. CoRR Shivam Barwey, Riccardo Balin, Bethany Lusch, Saumil Patel, Ramesh Balakrishnan, Pinaki Pal, Romit Maulik, Venkatram Vishwanath
2024	—	`conf`	Thorough Characterization and Analysis of Large Transformer Model Training At-Scale. SIGMETRICS/Performance (Abstracts) Scott Cheng, Jun-Liang Lin, Murali Emani, Siddhisanket Raskar, Sam Foreman, Zhen Xie, Venkatram Vishwanath, Mahmut T. Kandemir
2024	J	`jnl`	Thorough Characterization and Analysis of Large Transformer Model Training At-Scale. Proc. ACM Meas. Anal. Comput. Syst. Scott Cheng, Jun-Liang Lin, Murali Emani, Siddhisanket Raskar, Sam Foreman, Zhen Xie, Venkatram Vishwanath, Mahmut Taylan Kandemir
2024	—	`conf`	Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators. IPDPS (Workshops) Murali Emani, Sam Foreman, Varuni Sastry, Zhen Xie, Siddhisanket Raskar, William Arnold, Rajeev Thakur, Venkatram Vishwanath, Michael E. Papka, Sanjif Shanmugavelu, Darshan Gandhi, Hengyu Zhao, Dun Ma, Kiran Ranganath, Rick Weisner, Jiunn-Yeu Chen, Yuting Yang, Natalia Vassilieva, Bin C. Zhang, Sylvia Howland, Alexander Tsyplikhin
2024	—	`conf`	WActiGrad: Structured Pruning for Efficient Finetuning and Inference of Large Language Models on AI Accelerators. Euro-Par (2) Krishna Teja Chitty-Venkata, Varuni Katti Sastry, Murali Emani, Venkatram Vishwanath, Sanjif Shanmugavelu, Sylvia Howland
2023	J	`jnl`	A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators. CoRR Murali Emani, Sam Foreman, Varuni Sastry, Zhen Xie, Siddhisanket Raskar, William Arnold, Rajeev Thakur, Venkatram Vishwanath, Michael E. Papka
2023	J	`jnl`	A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems. CoRR Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma
2023	J	`jnl`	A Survey of Techniques for Optimizing Transformer Inference. CoRR Krishna Teja Chitty-Venkata, Sparsh Mittal, Murali Emani, Venkatram Vishwanath, Arun K. Somani
2023	J	`jnl`	A survey of techniques for optimizing transformer inference. J. Syst. Archit. Krishna Teja Chitty-Venkata, Sparsh Mittal, Murali Emani, Venkatram Vishwanath, Arun K. Somani
2023	B	`conf`	Asynchronous Decentralized Bayesian Optimization for Large Scale Hyperparameter Optimization. e-Science Romain Égelé, Isabelle Guyon, Venkatram Vishwanath, Prasanna Balaprakash
2023	—	`conf`	Characterizing the Performance of Triangle Counting on Graphcore's IPU Architecture. SC Workshops Reet Barik, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath
2023	J	`jnl`	DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl W. Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens
2023	—	`conf`	Demonstration of Portable Performance of Scientific Machine Learning on High Performance Computing Systems. SC Workshops Khalid Hossain, Riccardo Balin, Corey Adams, Thomas D. Uram, Kalyan Kumaran, Venkatram Vishwanath, Tanima Dey, Subrata Goswami, Janghaeng Lee, Rebecca Ramer, Koichi Yamada
2023	J	`jnl`	Differentiable Neural Architecture, Mixed Precision and Accelerator Co-Search. IEEE Access Krishna Teja Chitty-Venkata, Yiming Bian, Murali Emani, Venkatram Vishwanath, Arun K. Somani
2023	—	`conf`	Exploring the Use of Dataflow Architectures for Graph Neural Network Workloads. ISC Workshops Ryien Hosseini, Filippo Simini, Venkatram Vishwanath, Ramakrishnan Sivakumar, Sanjif Shanmugavelu, Zhengyu Chen, Lev Zlotnik, Mingran Wang, Philip Colangelo, Andrew Deng, Philip Lassen, Shukur Pathan
2023	J	`jnl`	GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. Int. J. High Perform. Comput. Appl. Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, Defne G. Ozgulbas, Natalia Vassilieva, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan
2023	J	`jnl`	Neural Architecture Search Benchmarks: Insights and Survey. IEEE Access Krishna Teja Chitty-Venkata, Murali Emani, Venkatram Vishwanath, Arun K. Somani
2023	J	`jnl`	Parallel Multi-Objective Hyperparameter Optimization with Uniform Normalization and Bounded Objectives. CoRR Romain Egele, Tyler H. Chang, Yixuan Sun, Venkatram Vishwanath, Prasanna Balaprakash
2023	—	`conf`	Scalable Lead Prediction with Transformers using HPC resources. SC Workshops Archit Vasan, Thomas S. Brettin, Rick Stevens, Arvind Ramanathan, Venkatram Vishwanath
2023	—	`conf`	TrainBF: High-Performance DNN Training Engine Using BFloat16 on AI Accelerators. Euro-Par Zhen Xie, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath
2022	—	`conf`	A Comprehensive Evaluation of Novel AI Accelerators for Deep Learning Workloads. PMBS@SC Murali Emani, Zhen Xie, Siddhisanket Raskar, Varuni Sastry, William Arnold, Bruce Wilson, Rajeev Thakur, Venkatram Vishwanath, Zhengchun Liu, Michael E. Papka, Cindy Orozco Bohorquez, Rick Weisner, Karen Li, Yongning Sheng, Yun Du, Jian Zhang, Alexander Tsyplikhin, Gurdaman Khaira, Jeremy Fowers, Ramakrishnan Sivakumar, Victoria Godsoe, Adrián Macías, Chetan Tekur, Matthew Boyd
2022	—	`conf`	AI Benchmarking for Science: Efforts from the MLCommons Science Working Group. ISC Workshops Jeyan Thiyagalingam, Gregor von Laszewski, Junqi Yin, Murali Emani, Juri Papay, Gregg Barrett, Piotr Luszczek, Aristeidis Tsaris, Christine R. Kirkpatrick, Feiyi Wang, Tom Gibbs, Venkatram Vishwanath, Mallikarjun Shankar, Geoffrey C. Fox, Tony Hey
2022	J	`jnl`	Asynchronous Distributed Bayesian Optimization at HPC Scale. CoRR Romain Egele, Joceran Gouneau, Venkatram Vishwanath, Isabelle Guyon, Prasanna Balaprakash
2022	A	`conf`	Efficient Design Space Exploration for Sparse Mixed Precision Neural Architectures. HPDC Krishna Teja Chitty-Venkata, Murali Emani, Venkatram Vishwanath, Arun K. Somani
2022	B	`conf`	HDF5 Cache VOL: Efficient and Scalable Parallel I/O through Caching Data on Node-local Storage. CCGRID Huihuo Zheng, Venkatram Vishwanath, Quincey Koziol, Houjun Tang, John Ravi, John Mainzer, Suren Byna
2022	J	`jnl`	Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action. Int. J. High Perform. Comput. Appl. Anda Trifan, Defne Gorgun, Michael Salim, Zongyi Li, Alexander Brace, Maxim Zvyagin, Heng Ma, Austin Clyde, David Clark, David J. Hardy, Tom Burnley, Lei Huang, John D. McCalpin, Murali Emani, Hyenseung Yoo, Junqi Yin, Aristeidis Tsaris, Vishal Subbiah, Tanveer Raza, Jessica Liu, Noah Trebesch, Geoffrey Wells, Venkatesh Mysore, Tom Gibbs, James C. Phillips, S. Chakra Chennubhotla, Ian T. Foster, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, John E. Stone, Emad Tajkhorshid, Sarah A. Harris, Arvind Ramanathan
2022	J	`jnl`	Neural Architecture Search for Transformers: A Survey. IEEE Access Krishna Teja Chitty-Venkata, Murali Emani, Venkatram Vishwanath, Arun K. Somani
2022	J	`jnl`	Operation-Level Performance Benchmarking of Graph Neural Networks for Scientific Applications. CoRR Ryien Hosseini, Filippo Simini, Venkatram Vishwanath
2022	J	`jnl`	PythonFOAM: In-situ data analyses with OpenFOAM and Python. J. Comput. Sci. Romit Maulik, Dimitrios Fytanidis, Bethany Lusch, Venkatram Vishwanath, Saumil Patel
2022	B	`conf`	Stimulus: Accelerate Data Management for Scientific AI applications in HPC. CCGRID Hariharan Devarajan, Anthony Kougkas, Huihuo Zheng, Venkatram Vishwanath, Xian-He Sun
2022	B	`conf`	Toward an In-Depth Analysis of Multifidelity High Performance Computing Systems. CCGRID Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma
2021	J	`jnl`	Accelerating Scientific Applications With SambaNova Reconfigurable Dataflow Architecture. Comput. Sci. Eng. Murali Emani, Venkatram Vishwanath, Corey Adams, Michael E. Papka, Rick Stevens, Laura Florescu, Sumti Jairath, William Liu, Tejas Nama, Arvind Sujeeth, Volodymyr V. Kindratenko, Anne C. Elster
2021	A	`conf`	AgEBO-tabular: joint neural architecture and hyperparameter search with autotuned data-parallel training for tabular data. SC Romain Égelé, Prasanna Balaprakash, Isabelle Guyon, Venkatram Vishwanath, Fangfang Xia, Rick Stevens, Zhengying Liu
2021	B	`conf`	DLIO: A Data-Centric Benchmark for Scientific Deep Learning Applications. CCGRID Hariharan Devarajan, Huihuo Zheng, Anthony Kougkas, Xian-He Sun, Venkatram Vishwanath
2021	J	`jnl`	MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. CoRR Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin
2021	—	`conf`	MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. MLHPC@SC Steven Farrell, Murali Emani, Jacob Balma, Lukas Drescher, Aleksandr Drozd, Andreas Fink, Geoffrey C. Fox, David Kanter, Thorsten Kurth, Peter Mattson, Dawei Mu, Amit Ruhela, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin
2021	J	`jnl`	PythonFOAM: In-situ data analyses with OpenFOAM and Python. CoRR Romit Maulik, Dimitrios Fytanidis, Bethany Lusch, Venkatram Vishwanath, Saumil Patel
2021	—	`conf`	Stream-AI-MD: streaming AI-driven adaptive molecular simulations for heterogeneous computing platforms. PASC Alexander Brace, Michael Salim, Vishal Subbiah, Heng Ma, Murali Emani, Anda Trifan, Austin R. Clyde, Corey Adams, Thomas D. Uram, Hyun Seung Yoo, Andew Hock, Jessica Liu, Venkatram Vishwanath, Arvind Ramanathan
2020	J	`jnl`	A machine learning workflow for molecular analysis: application to melting points. Mach. Learn. Sci. Technol. Ganesh Sivaraman, Nicholas E. Jackson, Benjamín Sánchez-Lengeling, Álvaro Vázquez-Mayagoitia, Alán Aspuru-Guzik, Venkatram Vishwanath, Juan J. de Pablo
2020	J	`jnl`	A terminology for in situ visualization and analysis systems. Int. J. High Perform. Comput. Appl. Hank Childs, Sean Ahern, James P. Ahrens, Andrew C. Bauer, Janine Bennett, E. Wes Bethel, Peer-Timo Bremer, Eric Brugger, Joseph Cottam, Matthieu Dorier, Soumya Dutta, Jean M. Favre, Thomas Fogal, Steffen Frey, Christoph Garth, Berk Geveci, William F. Godoy, Charles D. Hansen, Cyrus Harrison, Bernd Hentschel, Joseph A. Insley, Christopher R. Johnson, Scott Klasky, Aaron Knoll, James Kress, Matthew Larsen, Jay F. Lofstead, Kwan-Liu Ma, Preeti Malakar, Jeremy S. Meredith, Kenneth Moreland, Paul A. Navrátil, Patrick O'Leary, Manish Parashar, Valerio Pascucci, John Patchett, Tom Peterka, Steve Petruzza, Norbert Podhorszki, David Pugmire, Michel E. Rasquin, Silvio Rizzi, David H. Rogers, Sudhanshu Sane, Franz Sauer, Robert Sisneros, Han-Wei Shen, Will Usher, Rhonda Vickery, Venkatram Vishwanath, Ingo Wald, Ruonan Wang, Gunther H. Weber, Brad Whitlock, Matthew Wolf, Hongfeng Yu, Sean B. Ziegeler
2020	J	`jnl`	AgEBO-Tabular: Joint Neural Architecture and Hyperparameter Search with Autotuned Data-Parallel Training for Tabular Data. CoRR Romain Egele, Prasanna Balaprakash, Venkatram Vishwanath, Isabelle Guyon, Zhengying Liu
2020	J	`jnl`	ExaHDF5: Delivering Efficient Parallel I/O on Exascale Computing Systems. J. Comput. Sci. Technol. Suren Byna, M. Scot Breitenfeld, Bin Dong, Quincey Koziol, Elena Pourmal, Dana Robinson, Jérome Soumagne, Houjun Tang, Venkatram Vishwanath, Richard Warren
2020	A	`conf`	SeeSAw: Optimizing Performance of In-Situ Analytics Applications under Power Constraints. IPDPS Ivana Marincic, Venkatram Vishwanath, Henry Hoffmann
2019	J	`jnl`	A Benchmarking Study to Evaluate Apache Spark on Large-Scale Supercomputers. CoRR George K. Thiruvathukal, Cameron Christensen, Xiaoyong Jin, François Tessier, Venkatram Vishwanath
2019	J	`jnl`	Balsam: Automated Scheduling and Execution of Dynamic, Data-Intensive HPC Workflows. CoRR Michael A. Salim, Thomas D. Uram, J. Taylor Childers, Prasanna Balaprakash, Venkatram Vishwanath, Michael E. Papka
2019	—	`conf`	Balsam: Near Real-Time Experimental Data Analysis on Supercomputers. XLOOP@SC Michael A. Salim, Thomas D. Uram, J. Taylor Childers, Venkatram Vishwanath, Michael E. Papka
2019	—	`conf`	MELA: A Visual Analytics Tool for Studying Multifidelity HPC System Logs. DAAC@SC Shilpika, Bethany Lusch, Murali Emani, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma
2019	J	`jnl`	Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research. CoRR Prasanna Balaprakash, Romain Egele, Misha Salim, Stefan M. Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens
2019	A	`conf`	Scalable reinforcement-learning-based neural architecture search for cancer deep learning research. SC Prasanna Balaprakash, Romain Egele, Misha Salim, Stefan M. Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, Rick Stevens
2019	—	`conf`	Scaling Distributed Training of Flood-Filling Networks on HPC Infrastructure for Brain Mapping. DLS@SC Wushi Dong, Nicola J. Ferrier, Narayanan Kasthuri, Peter Littlewood, Murat Keçeli, Rafael Vescovi, Hanyu Li, Corey Adams, Elise Jennings, Samuel Flender, Thomas D. Uram, Venkatram Vishwanath
2019	J	`jnl`	Scaling Distributed Training of Flood-Filling Networks on HPC Infrastructure for Brain Mapping. CoRR Wushi Dong, Murat Keçeli, Rafael Vescovi, Hanyu Li, Corey Adams, Thomas D. Uram, Venkatram Vishwanath, Bobby Kasthuri, Nicola J. Ferrier, Peter Littlewood
2018	—	`conf`	Benchmarking Machine Learning Methods for Performance Modeling of Scientific Applications. PMBS@SC Preeti Malakar, Prasanna Balaprakash, Venkatram Vishwanath, Vitali A. Morozov, Kalyan Kumaran
2018	A	`conf`	Optimizing Data Aggregation by Leveraging the Deep Memory Hierarchy on Large-scale Systems. ICS François Tessier, Paul Gressier, Venkatram Vishwanath
2018	A	`conf`	Topology-aware space-shared co-analysis of large-scale molecular dynamics simulations. SC Preeti Malakar, Todd S. Munson, Christopher Knight, Venkatram Vishwanath, Michael E. Papka
2018	B	`conf`	Toward Scalable and Asynchronous Object-Centric Data Management for HPC. CCGrid Houjun Tang, Suren Byna, Francois Tessier, Teng Wang, Bin Dong, Jingqing Mu, Quincey Koziol, Jérome Soumagne, Venkatram Vishwanath, Jialin Liu, Richard Warren
2018	—	`conf`	libIS: a lightweight library for flexible in transit visualization. ISAV@SC Will Usher, Silvio Rizzi, Ingo Wald, Jefferson Amstutz, Joseph A. Insley, Venkatram Vishwanath, Nicola J. Ferrier, Michael E. Papka, Valerio Pascucci
2017	—	`conf`	A Visual Analytics System for Optimizing Communications in Massively Parallel Applications. VAST Takanori Fujiwara, Preeti Malakar, Khairi Reda, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma
2017	—	`conf`	A distributed graph approach for pre-processing linked RDF data using supercomputers. SBD@SIGMOD Michael J. Lewis, George K. Thiruvathukal, Venkatram Vishwanath, Michael E. Papka, Andrew E. Johnson
2017	—	`conf`	Analytical Performance Modeling and Validation of Intel's Xeon Phi Architecture. Conf. Computing Frontiers Sudheer Chunduri, Prasanna Balaprakash, Vitali A. Morozov, Venkatram Vishwanath, Kalyan Kumaran
2017	J	`jnl`	Data movement optimizations for independent MPI I/O on the Blue Gene/Q. Parallel Comput. Preeti Malakar, Venkatram Vishwanath
2017	J	`jnl`	HACC: extreme scaling and performance across diverse architectures. Commun. ACM Salman Habib, Vitali A. Morozov, Nicholas Frontiere, Hal Finkel, Adrian Pope, Katrin Heitmann, Kalyan Kumaran, Venkatram Vishwanath, Tom Peterka, Joseph A. Insley, David Daniel, Patricia K. Fasel, Zarija Lukic
2017	J	`jnl`	Hierarchical Read-Write Optimizations for Scientific Applications with Multi-variable Structured Datasets. Int. J. Parallel Program. Preeti Malakar, Venkatram Vishwanath
2017	—	`conf`	PoLiMEr: An Energy Monitoring and Power Limiting Interface for HPC Applications. E2SC@SC Ivana Marincic, Venkatram Vishwanath, Henry Hoffmann
2017	—	`conf`	Scalable In situ Analysis of Molecular Dynamics Simulations. ISAV@SC Preeti Malakar, Christopher Knight, Todd S. Munson, Venkatram Vishwanath, Michael E. Papka
2017	C	`conf`	TAPIOCA: An I/O Library for Optimized Topology-Aware Data Aggregation on Large-Scale Supercomputers. CLUSTER Francois Tessier, Venkatram Vishwanath, Emmanuel Jeannot
2016	A	`conf`	A data driven scheduling approach for power management on HPC systems. SC Sean Wallace, Xu Yang, Venkatram Vishwanath, William E. Allcock, Susan Coghlan, Michael E. Papka, Zhiling Lan
2016	J	`jnl`	Application power profiling on IBM Blue Gene/Q. Parallel Comput. Sean Wallace, Zhou Zhou, Venkatram Vishwanath, Susan Coghlan, John R. Tramm, Zhiling Lan, Michael E. Papka
2016	—	`conf`	Coupling LAMMPS and the vl3 Framework for Co-Visualization of Atomistic Simulations. IPDPS Workshops Silvio Rizzi, Mark Hereld, Joseph A. Insley, Preeti Malakar, Michael E. Papka, Thomas D. Uram, Venkatram Vishwanath
2016	—	`conf`	Early Investigations into Using a Remote RAM Pool with the vl3 Visualization Framework. ISAV@SC Dawid Zawislak, Brian R. Toonen, William E. Allcock, Silvio Rizzi, Joseph A. Insley, Venkatram Vishwanath, Michael E. Papka
2016	J	`jnl`	Improving sparse data movement performance using multiple paths on the Blue Gene/Q supercomputer. Parallel Comput. Huy Bui, Eun-Sung Jung, Venkatram Vishwanath, Andrew E. Johnson, Jason Leigh, Michael E. Papka
2016	A	`conf`	Optimal execution of co-analysis for large-scale molecular dynamics simulations. SC Preeti Malakar, Venkatram Vishwanath, Christopher Knight, Todd S. Munson, Michael E. Papka
2016	—	`conf`	Parallel distributed, GPU-accelerated, advanced lighting calculations for large-scale volume visualization. LDAV Min Shih, Silvio Rizzi, Joseph A. Insley, Thomas D. Uram, Venkatram Vishwanath, Mark Hereld, Michael E. Papka, Kwan-Liu Ma
2016	A	`conf`	Performance analysis, design considerations, and applications of extreme-scale SC 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	—	`conf`	Topology-Aware Data Aggregation for Intensive I/O on Large-Scale Supercomputers. COMHPC@SC Francois Tessier, Preeti Malakar, Venkatram Vishwanath, Emmanuel Jeannot, Florin Isaila
2016	J	`jnl`	Workflow performance improvement using model-based scheduling over multiple clusters and clouds. Future Gener. Comput. Syst. Ketan Maheshwari, Eun-Sung Jung, Jiayuan Meng, Vitali A. Morozov, Venkatram Vishwanath, Rajkumar Kettimuthu
2015	J	`jnl`	Cluster-to-cluster data transfer with data compression over wide-area networks. J. Parallel Distributed Comput. Eun-Sung Jung, Rajkumar Kettimuthu, Venkatram Vishwanath
2015	C	`conf`	Comparison of Vendor Supplied Environmental Data Collection Mechanisms. CLUSTER Sean Wallace, Venkatram Vishwanath, Susan Coghlan, Zhiling Lan, Michael E. Papka
2015	Misc	`conf`	Improving Communication Throughput by Multipath Load Balancing on Blue Gene/Q. HiPC Huy Bui, Preeti Malakar, Venkatram Vishwanath, Todd S. Munson, Eun-Sung Jung, Andrew E. Johnson, Michael E. Papka, Jason Leigh
2015	—	`conf`	Large-Scale Parallel Visualization of Particle-Based Simulations using Point Sprites and Level-Of-Detail. EGPGV@EuroVis Silvio Rizzi, Mark Hereld, Joseph A. Insley, Michael E. Papka, Thomas D. Uram, Venkatram Vishwanath
2015	—	`conf`	Large-scale co-visualization for LAMMPS using vl3. LDAV Silvio Rizzi, Mark Hereld, Joseph A. Insley, Michael E. Papka, Thomas D. Uram, Venkatram Vishwanath
2015	—	`conf`	Modeling Cooperative Threads to Project GPU Performance for Adaptive Parallelism. IPDPS Workshops Jiayuan Meng, Thomas D. Uram, Vitali A. Morozov, Venkatram Vishwanath, Kalyan Kumaran
2015	C	`conf`	Multipath Load Balancing for M × N Communication Patterns on the Blue Gene/Q Supercomputer Interconnection Network. CLUSTER Huy Bui, Robert L. Jacob, Preeti Malakar, Venkatram Vishwanath, Andrew E. Johnson, Michael E. Papka, Jason Leigh
2015	A	`conf`	Optimal scheduling of in-situ analysis for large-scale scientific simulations. SC Preeti Malakar, Venkatram Vishwanath, Todd S. Munson, Christopher Knight, Mark Hereld, Sven Leyffer, Michael E. Papka
2015	Misc	`conf`	Profiling transport performance for big data transfer over dedicated channels. ICNC Daqing Yun, Chase Qishi Wu, Nageswara S. V. Rao, Bradley W. Settlemyer, Josh Lothian, Rajkumar Kettimuthu, Venkatram Vishwanath
2015	—	`conf`	Route-aware independent MPI I/O on the blue gene/Q. DISCS@SC Preeti Malakar, Venkatram Vishwanath
2015	—	`conf`	Streaming ultra high resolution images to large tiled display at nearly interactive frame rate with vl3. LDAV Jie Jiang, Mark Hereld, Joseph A. Insley, Michael E. Papka, Silvio Rizzi, Thomas D. Uram, Venkatram Vishwanath
2015	—	`conf`	TECA: Petascale Pattern Recognition for Climate Science. CAIP (2) Prabhat, Surendra Byna, Venkatram Vishwanath, Eli Dart, Michael F. Wehner, William D. Collins
2014	—	`ed.`	4th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2014, Paris, France, November 9-10, 2014 LDAV Hank Childs, Renato Pajarola, Venkatram Vishwanath
2014	J	`jnl`	DIRAQ: scalable in situ data- and resource-aware indexing for optimized query performance. Clust. Comput. Sriram Lakshminarasimhan, Xiaocheng Zou, David A. Boyuka II, Saurabh V. Pendse, John Jenkins, Venkatram Vishwanath, Michael E. Papka, Scott Klasky, Nagiza F. Samatova
2014	—	`conf`	Distributed multipath routing algorithm for data center networks. DISCS@SC Eun-Sung Jung, Venkatram Vishwanath, Rajkumar Kettimuthu
2014	A	`conf`	Efficient I/O and Storage of Adaptive-Resolution Data. SC Sidharth Kumar, John Edwards, Peer-Timo Bremer, Aaron Knoll, Cameron Christensen, Venkatram Vishwanath, Philip H. Carns, John A. Schmidt, Valerio Pascucci
2014	C	`conf`	Fast Multiresolution Reads of Massive Simulation Datasets. ISC Sidharth Kumar, Cameron Christensen, John A. Schmidt, Peer-Timo Bremer, Eric Brugger, Venkatram Vishwanath, Philip H. Carns, Hemanth Kolla, Ray W. Grout, Jacqueline Chen, Martin Berzins, Giorgio Scorzelli, Valerio Pascucci
2014	—	`conf`	Improving Data Movement Performance for Sparse Data Patterns on the Blue Gene/Q Supercomputer. ICPP Workshops Huy Bui, Jason Leigh, Eun-Sung Jung, Venkatram Vishwanath, Michael E. Papka
2014	B	`conf`	Improving Multisite Workflow Performance Using Model-Based Scheduling. ICPP Ketan Maheshwari, Eun-Sung Jung, Jiayuan Meng, Venkatram Vishwanath, Rajkumar Kettimuthu
2014	J	`jnl`	Large-Scale Simulations of Sky Surveys. Comput. Sci. Eng. Katrin Heitmann, Salman Habib, Hal Finkel, Nicholas Frontiere, Adrian Pope, Vitali A. Morozov, Steve Rangel, Eve Kovacs, Juliana Kwan, Nan Li, Silvio Rizzi, Joseph A. Insley, Venkatram Vishwanath, Tom Peterka, David Daniel, Patricia K. Fasel, George Zagaris
2014	—	`conf`	Performance Modeling of vl3 Volume Rendering on GPU-Based Clusters. EGPGV@EuroVis Silvio Rizzi, Mark Hereld, Joseph A. Insley, Michael E. Papka, Thomas D. Uram, Venkatram Vishwanath
2014	—	`conf`	SKOPE: a framework for modeling and exploring workload behavior. Conf. Computing Frontiers Jiayuan Meng, Xingfu Wu, Vitali A. Morozov, Venkatram Vishwanath, Kalyan Kumaran, Valerie E. Taylor
2014	C	`conf`	Scalable Parallel I/O on a Blue Gene/Q Supercomputer Using Compression, Topology-Aware Data Aggregation, and Subfiling. PDP Huy Bui, Hal Finkel, Venkatram Vishwanath, Salman Habib, Katrin Heitmann, Jason Leigh, Michael E. Papka, Kevin Harms
2013	—	`conf`	A Generic High-Performance Method for Deinterleaving Scientific Data. Euro-Par Eric R. Schendel, Steve Harenberg, Houjun Tang, Venkatram Vishwanath, Michael E. Papka, Nagiza F. Samatova
2013	C	`conf`	Application power profiling on IBM Blue Gene/Q. CLUSTER Sean Wallace, Venkatram Vishwanath, Susan Coghlan, John R. Tramm, Zhiling Lan, Michael E. Papka
2013	B	`conf`	Characterization and Understanding Machine-Specific Interconnects. PaCT Vitali A. Morozov, Jiayuan Meng, Venkatram Vishwanath, Kalyan Kumaran, Michael E. Papka
2013	A	`conf`	Characterization and modeling of PIDX parallel I/O for performance optimization. SC 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	A	`conf`	Early Experience on the Blue Gene/Q Supercomputing System. IPDPS Vitali A. Morozov, Kalyan Kumaran, Venkatram Vishwanath, Jiayuan Meng, Michael E. Papka
2013	—	`conf`	Efficient parallel volume rendering of large-scale adaptive mesh refinement data. LDAV Nick Leaf, Venkatram Vishwanath, Joseph A. Insley, Mark Hereld, Michael E. Papka, Kwan-Liu Ma
2013	—	`ed.`	IEEE Symposium on Large-Scale Data Analysis and Visualization, LDAV 2013, 13-14 October, 2013, Atlanta, Georgia, USA LDAV Berk Geveci, Hanspeter Pfister, Venkatram Vishwanath
2013	—	`conf`	Measuring Power Consumption on IBM Blue Gene/Q. IPDPS Workshops Sean Wallace, Venkatram Vishwanath, Susan Coghlan, Zhiling Lan, Michael E. Papka
2013	C	`conf`	Model-driven multisite workflow scheduling. CLUSTER Ketan Maheshwari, Eun-Sung Jung, Jiayuan Meng, Venkatram Vishwanath, Rajkumar Kettimuthu
2013	J	`jnl`	Multi-domain job coscheduling for leadership computing systems. J. Supercomput. Wei Tang, Narayan Desai, Venkatram Vishwanath, Daniel Buettner, Zhiling Lan
2013	—	`conf`	On-demand unstructured mesh translation for reducing memory pressure during in situ analysis. UltraVis@SC Jonathan Woodring, James P. Ahrens, Timothy J. Tautges, Tom Peterka, Venkatram Vishwanath, Berk Geveci
2013	—	`conf`	Proactive Support for Large-Scale Data Exploration. IPDPS Workshops Mark Hereld, Tanu Malik, Venkatram Vishwanath
2013	—	`ed.`	Proceedings of the 8th International Workshop on Ultrascale Visualization, UltraVis 2013, Denver, Colorado, USA, November 17-21, 2013 UltraVis@SC Kwan-Liu Ma, Venkatram Vishwanath, Hongfeng Yu
2013	A	`conf`	Scalable in situ scientific data encoding for analytical query processing. HPDC Sriram Lakshminarasimhan, David A. Boyuka II, Saurabh V. Pendse, Xiaocheng Zou, John Jenkins, Venkatram Vishwanath, Michael E. Papka, Nagiza F. Samatova
2013	—	`conf`	Toward optimizing disk-to-disk transfer on 100G networks. IEEE ANTS Eun-Sung Jung, Rajkumar Kettimuthu, Venkatram Vishwanath
2012	—	`conf`	ALCF MPI Benchmarks: Understanding Machine-Specific Communication Behavior. ICPP Workshops Vitali A. Morozov, Jiayuan Meng, Venkatram Vishwanath, Jeff R. Hammond, Kalyan Kumaran, Michael E. Papka
2012	—	`conf`	Abstract: Evaluating Communication Performance in BlueGene/Q and Cray XE6 Supercomputers. SC Companion Huy Bui, Venkatram Vishwanath, Jason Leigh, Michael E. Papka
2012	—	`conf`	Accelerating Data Movement Leveraging End-System and Network Parallelism. SC Companion Jun Yi, Rajkumar Kettimuthu, Venkatram Vishwanath
2012	A	`conf`	Dataflow-driven GPU performance projection for multi-kernel transformations. SC Jiayuan Meng, Vitali A. Morozov, Venkatram Vishwanath, Kalyan Kumaran
2012	A	`conf`	Efficient data restructuring and aggregation for I/O acceleration in PIDX. SC 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	C	`conf`	Evaluating Power-Monitoring Capabilities on IBM Blue Gene/P and Blue Gene/Q. CLUSTER Kazutomo Yoshii, Kamil Iskra, Rinku Gupta, Peter H. Beckman, Venkatram Vishwanath, Chenjie Yu, Susan Coghlan
2012	—	`conf`	Poster: Evaluating Communication Performance in BlueGene/Q and Cray XE6 Supercomputers. SC Companion Huy Bui, Venkatram Vishwanath, Jason Leigh, Michael E. Papka
2011	—	`conf`	Electronic poster: co-visualization of full data and in situ data extracts from unstructured grid cfd at 160k cores. SC Companion 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	—	`conf`	Exploring large data over wide area networks. LDAV Mark Hereld, Joseph A. Insley, Eric C. Olson, Michael E. Papka, Venkatram Vishwanath, Michael L. Norman, Rick Wagner
2011	A	`conf`	GROPHECY: GPU performance projection from CPU code skeletons. SC Jiayuan Meng, Vitali A. Morozov, Kalyan Kumaran, Venkatram Vishwanath, Thomas D. Uram
2011	—	`conf`	Job Coscheduling on Coupled High-End Computing Systems. ICPP Workshops Wei Tang, Narayan Desai, Venkatram Vishwanath, Daniel Buettner, Zhiling Lan
2011	—	`conf`	Modeling early galaxies using radiation hydrodynamics. SC Companion Joseph A. Insley, Rick Wagner, Robert Harkness, Daniel R. Reynolds, Michael L. Norman, Mark Hereld, Eric C. Olson, Michael E. Papka, Venkatram Vishwanath
2011	C	`conf`	PIDX: Efficient Parallel I/O for Multi-resolution Multi-dimensional Scientific Datasets. CLUSTER Sidharth Kumar, Venkatram Vishwanath, Philip H. Carns, Brian Summa, Giorgio Scorzelli, Valerio Pascucci, Robert B. Ross, Jacqueline Chen, Hemanth Kolla, Ray W. Grout
2011	A	`conf`	Topology-aware data movement and staging for I/O acceleration on Blue Gene/P supercomputing systems. SC Venkatram Vishwanath, Mark Hereld, Vitali A. Morozov, Michael E. Papka
2011	—	`conf`	Toward simulation-time data analysis and I/O acceleration on leadership-class systems. LDAV Venkatram Vishwanath, Mark Hereld, Michael E. Papka
2010	A	`conf`	Accelerating I/O Forwarding in IBM Blue Gene/P Systems. SC Venkatram Vishwanath, Mark Hereld, Kamil Iskra, Dries Kimpe, Vitali A. Morozov, Michael E. Papka, Robert B. Ross, Kazutomo Yoshii
2010	A	`conf`	Multi-application inter-tile synchronization on ultra-high-resolution display walls. MMSys Sungwon Nam, Sachin Deshpande, Venkatram Vishwanath, Byungil Jeong, Luc Renambot, Jason Leigh
2009	J	`jnl`	Accelerating tropical cyclone analysis using LambdaRAM, a distributed data cache over wide-area ultra-fast networks. Future Gener. Comput. Syst. Venkatram Vishwanath, Robert Burns, Jason Leigh, Michael S. Seablom
2009	J	`jnl`	The OptIPortal, a scalable visualization, storage, and computing interface device for the OptiPuter. Future Gener. Comput. Syst. Thomas A. DeFanti, Jason Leigh, Luc Renambot, Byungil Jeong, Alan Verlo, Lance Long, Maxine D. Brown, Daniel J. Sandin, Venkatram Vishwanath, Qian Liu, Mason J. Katz, Philip M. Papadopoulos, Joseph P. Keefe, Gregory R. Hidley, Gregory Dawe, Ian Kaufman, Bryan Glogowski, Kai-Uwe Doerr, Rajvikram Singh, Javier Girado
2008	C	`conf`	Specification and Verification of LambdaRAM: A Wide-area Distributed Cache for High Performance Computing. MEMOCODE Venkatram Vishwanath, Lenore D. Zuck, Jason Leigh
2008	—	`conf`	The Rails Toolkit - Enabling End-System Topology-Aware High End Computing. eScience Venkatram Vishwanath, Jason Leigh, Sungwon Nam, Luc Renambot, Takashi Shimizu, Hirokazu Takahashi, Makoto Takizawa, Osamu Kamatani
2006	B	`conf`	AR-PIN/PDC: Flexible Advance Reservation of Intradomain and Interdomain Lightpaths. GLOBECOM Eric He, Xi Wang, Venkatram Vishwanath, Jason Leigh
2006	C	`conf`	LambdaBridge: A Scalable Architecture for Future Generation Terabit Applications. BROADNETS Xi Wang, Venkatram Vishwanath, Byungil Jeong, Ratko Jagodic, Eric He, Luc Renambot, Andrew E. Johnson, Jason Leigh
2006	J	`jnl`	The first functional demonstration of optical virtual concatenation as a technique for achieving Terabit networking. Future Gener. Comput. Syst. Akira Hirano, Luc Renambot, Byungil Jeong, Jason Leigh, Alan Verlo, Venkatram Vishwanath, Rajvikram Singh, Julieta Aguilera, Andrew E. Johnson, Thomas A. DeFanti, Lance Long, Nicholas Schwarz, Maxine D. Brown, Naohide Nagatsu, Yukio Tsukishima, Masahito Tomizawa, Yutaka Miyamoto, Masahiko Jinno, Yoshihiro Takigawa, Osamu Ishida
2006	J	`jnl`	The global lambda visualization facility: An international ultra-high-definition wide-area visualization collaboratory. Future Gener. Comput. Syst. Jason Leigh, Luc Renambot, Andrew E. Johnson, Byungil Jeong, Ratko Jagodic, Nicholas Schwarz, Dmitry Svistula, Rajvikram Singh, Julieta Aguilera, Xi Wang, Venkatram Vishwanath, Brenda Lopez, Daniel J. Sandin, Tom Peterka, Javier Girado, Robert Kooima, Jinghua Ge, Lance Long, Alan Verlo, Thomas A. DeFanti, Maxine D. Brown, Donna J. Cox, Robert Patterson, Patrick Dorn, Paul Wefel, Stuart Levy, Jonas Talandis, Joe Reitzer, Tom Prudhomme, Tom Coffin, Brian Davis, Paul Wielinga, Bram Stolk, Gee Bum Koo, Jaeyoun Kim, Sangwoo Han, JongWon Kim, Brian Corrie II, Todd Zimmerman, Pierre Boulanger, Manuel Garcia
2004	C	`conf`	JuxtaView - a tool for interactive visualization of large imagery on scalable tiled displays. CLUSTER Naveen K. Krishnaprasad, Venkatram Vishwanath, Shalini Venkataraman, A. G. Rao, Luc Renambot, Jason Leigh, Andrew E. Johnson, Brian Davis
2004	A	`conf`	Vol-a-Tile - A Tool for Interactive Exploration of Large Volumetric Data on Scalable Tiled Displays. IEEE Visualization Nicholas Schwarz, Shalini Venkataraman, Luc Renambot, Naveen K. Krishnaprasad, Venkatram Vishwanath, Jason Leigh, Andrew E. Johnson, Graham Kent, Atul Nayak