Murali Emani

According to our database, Murali Emani authored at least 54 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

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 Taylan Kandemir

Proc. ACM Meas. Anal. Comput. Syst., 2024

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

CoRR, 2024

AI-coupled HPC Workflow Applications, Middleware and Performance.

Wes Brewer, Ana Gainaru, Frédéric Suter, Feiyi Wang, Murali Emani, Shantenu Jha

CoRR, 2024

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

Proceedings of the 2024 USENIX Annual Technical Conference, 2024

MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows with Direct Preference Optimization.

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

Proceedings of the International Conference for High Performance Computing, 2024

Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators.

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

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

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

Proceedings of the Euro-Par 2024: Parallel Processing, 2024

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

Proceedings of the 24th IEEE International Symposium on Cluster, 2024

2023

A survey of techniques for optimizing transformer inference.

Krishna Teja Chitty-Venkata, Sparsh Mittal, Murali Emani, Venkatram Vishwanath, Arun K. Somani

J. Syst. Archit., November, 2023

GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics.

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

Int. J. High Perform. Comput. Appl., November, 2023

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.

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 Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens

CoRR, 2023

A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators.

Murali Emani, Sam Foreman, Varuni Sastry, Zhen Xie, Siddhisanket Raskar, William Arnold, Rajeev Thakur, Venkatram Vishwanath, Michael E. Papka

CoRR, 2023

Neural Architecture Search Benchmarks: Insights and Survey.

Krishna Teja Chitty-Venkata, Murali Emani, Venkatram Vishwanath, Arun K. Somani

IEEE Access, 2023

Differentiable Neural Architecture, Mixed Precision and Accelerator Co-Search.

Krishna Teja Chitty-Venkata, Yiming Bian, Murali Emani, Venkatram Vishwanath, Arun K. Somani

IEEE Access, 2023

HPC-GPT: Integrating Large Language Model for High-Performance Computing.

Xianzhong Ding, Le Chen, Murali Emani, Chunhua Liao, Pei-Hung Lin, Tristan Vanderbruggen, Zhen Xie, Alberto Cerpa, Wan Du

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Data Race Detection Using Large Language Models.

Le Chen, Xianzhong Ding, Murali Emani, Tristan Vanderbruggen, Pei-Hung Lin, Chunhua Liao

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Characterizing the Performance of Triangle Counting on Graphcore's IPU Architecture.

Reet Barik, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Transfer Learning Across Heterogeneous Features For Efficient Tensor Program Generation.

Gaurav Verma, Siddhisanket Raskar, Zhen Xie, Abid M. Malik, Murali Emani, Barbara M. Chapman

Proceedings of the 2nd International Workshop on Extreme Heterogeneity Solutions, 2023

LM4HPC: Towards Effective Language Model Application in High-Performance Computing.

Le Chen, Pei-Hung Lin, Tristan Vanderbruggen, Chunhua Liao, Murali Emani, Bronis R. de Supinski

Proceedings of the OpenMP: Advanced Task-Based, Device and Compiler Programming, 2023

TrainBF: High-Performance DNN Training Engine Using BFloat16 on AI Accelerators.

Zhen Xie, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath

Proceedings of the Euro-Par 2023: Parallel Processing - 29th International Conference on Parallel and Distributed Computing, Limassol, Cyprus, August 28, 2023

2022

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.

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

Int. J. High Perform. Comput. Appl., 2022

Towards Seamless Management of AI Models in High-Performance Computing.

Sixing Yu, Murali Emani, Chunhua Liao, Pei-Hung Lin, Tristan Vanderbruggen, Xipeng Shen, Ali Jannesari

CoRR, 2022

FAIR for AI: An interdisciplinary, international, inclusive, and diverse community building perspective.

Eliu A. Huerta, Ben Blaiszik, L. Catherine Brinson, Kristofer E. Bouchard, Daniel Diaz, Caterina Doglioni, Javier M. Duarte, Murali Emani, Ian T. Foster, Geoffrey C. Fox, Philip C. Harris, Lukas Heinrich, Shantenu Jha, Daniel S. Katz, Volodymyr V. Kindratenko, Christine R. Kirkpatrick, Kati Lassila-Perini, Ravi K. Madduri, Mark S. Neubauer, Fotis E. Psomopoulos, Avik Roy, Oliver Rübel, Zhizhen Zhao, Ruike Zhu

CoRR, 2022

XUnified: A Framework for Guiding Optimal Use of GPU Unified Memory.

Hailu Xu, Pei-Hung Lin, Murali Emani, Liting Hu, Chunhua Liao

IEEE Access, 2022

Neural Architecture Search for Transformers: A Survey.

Krishna Teja Chitty-Venkata, Murali Emani, Venkatram Vishwanath, Arun K. Somani

IEEE Access, 2022

Making Machine Learning Datasets and Models FAIR for HPC: A Methodology and Case Study.

Pei-Hung Lin, Chunhua Liao, Winson Chen, Tristan Vanderbruggen, Murali Emani, Hailu Xu

Proceedings of the Fourth International Conference on Transdisciplinary AI, 2022

AI Benchmarking for Science: Efforts from the MLCommons Science Working Group.

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

Proceedings of the High Performance Computing. ISC High Performance 2022 International Workshops - Hamburg, Germany, May 29, 2022

A Comprehensive Evaluation of Novel AI Accelerators for Deep Learning Workloads.

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

Proceedings of the IEEE/ACM International Workshop on Performance Modeling, 2022

Throughput-oriented and Accuracy-aware DNN Training with BFloat16 on GPU.

Zhen Xie, Siddhisanket Raskar, Murali Emani

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

Interactive NLU-Powered Ontology-Based Workflow Synthesis for FAIR Support of HPC.

Zifan Nan, Mithil Dave, Xipeng Shen, Chunhua Liao, Tristan Vanderbruggen, Pei-Hung Lin, Murali Emani

Proceedings of the IEEE/ACM International Workshop on HPC User Support Tools, 2022

Efficient Design Space Exploration for Sparse Mixed Precision Neural Architectures.

Krishna Teja Chitty-Venkata, Murali Emani, Venkatram Vishwanath, Arun K. Somani

Proceedings of the HPDC '22: The 31st International Symposium on High-Performance Parallel and Distributed Computing, Minneapolis, MN, USA, 27 June 2022, 2022

Finding Reusable Machine Learning Components to Build Programming Language Processing Pipelines.

Patrick J. Flynn, Tristan Vanderbruggen, Chunhua Liao, Pei-Hung Lin, Murali Emani, Xipeng Shen

Proceedings of the Software Architecture. ECSA 2022 Tracks and Workshops, 2022

Early Experience with Transformer-Based Similarity Analysis for DataRaceBench.

Winson Chen, Tristan Vanderbruggen, Pei-Hung Lin, Chunhua Liao, Murali Emani

Proceedings of the Sixth IEEE/ACM International Workshop on Software Correctness for HPC Applications, 2022

Towards neural architecture-aware exploration of compiler optimizations in a deep learning {graph} compiler.

Gaurav Verma, Swetang Finviya, Abid M. Malik, Murali Emani, Barbara M. Chapman

Proceedings of the CF '22: 19th ACM International Conference on Computing Frontiers, Turin, Italy, May 17, 2022

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

Proceedings of the 22nd IEEE International Symposium on Cluster, 2022

2021

Accelerating Scientific Applications With SambaNova Reconfigurable Dataflow Architecture.

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

Comput. Sci. Eng., 2021

MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems.

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

CoRR, 2021

Stream-AI-MD: streaming AI-driven adaptive molecular simulations for heterogeneous computing platforms.

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

Proceedings of the PASC '21: Platform for Advanced Scientific Computing Conference, 2021

HPCFAIR: Enabling FAIR AI for HPC Applications.

Gaurav Verma, Murali Emani, Chunhua Liao, Pei-Hung Lin, Tristan Vanderbruggen, Xipeng Shen, Barbara M. Chapman

Proceedings of the IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2021

HPC Ontology: Towards a Unified Ontology for Managing Training Datasets and AI Models for High-Performance Computing.

Chunhua Liao, Pei-Hung Lin, Gaurav Verma, Tristan Vanderbruggen, Murali Emani, Zifan Nan, Xipeng Shen

Proceedings of the IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2021

MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems.

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

Proceedings of the IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2021

2020

EReinit: Scalable and efficient fault-tolerance for bulk-synchronous MPI applications.

Sourav Chakraborty, Ignacio Laguna, Murali Emani, Kathryn M. Mohror, Dhabaleswar K. Panda, Martin Schulz, Hari Subramoni

Concurr. Comput. Pract. Exp., 2020

2019

Machine Learning Guided Optimal Use of GPU Unified Memory.

Hailu Xu, Murali Emani, Pei-Hung Lin, Liting Hu, Chunhua Liao

Proceedings of the 2019 IEEE/ACM Workshop on Memory Centric High Performance Computing, 2019

MELA: A Visual Analytics Tool for Studying Multifidelity HPC System Logs.

Shilpika, Bethany Lusch, Murali Emani, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma

Proceedings of the 3rd IEEE/ACM Industry/University Joint International Workshop on Data-center Automation, 2019

2018

Data Placement Optimization in GPU Memory Hierarchy using Predictive Modeling.

Larisa Stoltzfus, Murali Emani, Pei-Hung Lin, Chunhua Liao

Proceedings of the Workshop on Memory Centric High Performance Computing, 2018

Is Data Placement Optimization Still Relevant on Newer GPUs?

Md Abdullah Shahneous Bari, Larisa Stoltzfus, Pei-Hung Lin, Chunhua Liao, Murali Emani, Barbara M. Chapman

Proceedings of the 2018 IEEE/ACM Performance Modeling, 2018

MPI Stages: Checkpointing MPI State for Bulk Synchronous Applications.

Nawrin Sultana, Anthony Skjellum, Ignacio Laguna, Matthew Shane Farmer, Kathryn M. Mohror, Murali Emani

Proceedings of the 25th European MPI Users' Group Meeting, 2018

Bootstrapping Parameter Space Exploration for Fast Tuning.

Jayaraman J. Thiagarajan, Nikhil Jain, Rushil Anirudh, Alfredo Giménez, Rahul Sridhar, Aniruddha Marathe, Tao Wang, Murali Emani, Abhinav Bhatele, Todd Gamblin

Proceedings of the 32nd International Conference on Supercomputing, 2018

2016

Mapping Medley: Adaptive Parallelism Mapping with Varying Optimization Goals.

Murali Krishna Emani

Proceedings of the Languages and Compilers for Parallel Computing, 2016

Integrating Algorithmic Parameters into Benchmarking and Design Space Exploration in 3D Scene Understanding.

Bruno Bodin, Luigi Nardi, M. Zeeshan Zia, Harry Wagstaff, Govind Sreekar Shenoy, Murali Krishna Emani, John Mawer, Christos Kotselidis, Andy Nisbet, Mikel Luján, Björn Franke, Paul H. J. Kelly, Michael F. P. O'Boyle

Proceedings of the 2016 International Conference on Parallel Architectures and Compilation, 2016

2015

Adaptive parallelism mapping in dynamic environments using machine learning.

Murali Krishna Emani

PhD thesis, 2015

Celebrating diversity: a mixture of experts approach for runtime mapping in dynamic environments.

Murali Krishna Emani, Michael F. P. O'Boyle

Proceedings of the 36th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2015

2014

Change Detection Based Parallelism Mapping: Exploiting Offline Models and Online Adaptation.

Murali Krishna Emani, Michael F. P. O'Boyle

Proceedings of the Languages and Compilers for Parallel Computing, 2014

2013

Smart, adaptive mapping of parallelism in the presence of external workload.

Murali Krishna Emani, Zheng Wang, Michael F. P. O'Boyle

Proceedings of the 2013 IEEE/ACM International Symposium on Code Generation and Optimization, 2013