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Murali Emani
Murali Krishna Emani
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- affiliation: Argonne National Laboratory, IL, USA
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2020 – today
- 2024
- [j10]Scott Cheng
, Jun-Liang Lin
Thorough Characterization and Analysis of Large Transformer Model Training At-Scale. Proc. ACM Meas. Anal. Comput. Syst. 8(1): 8:1-8:25 (2024) - [c36]Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma:
A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems. CCGrid 2024: 478-488 - [c35]Krishna Teja Chitty-Venkata, Varuni Katti Sastry, Murali Emani, Venkatram Vishwanath, Sanjif Shanmugavelu, Sylvia Howland:
WActiGrad: Structured Pruning for Efficient Finetuning and Inference of Large Language Models on AI Accelerators. Euro-Par (2) 2024: 317-331 - [c34]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:
Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators. IPDPS (Workshops) 2024: 1-10 - [c33]Scott Cheng
Thorough Characterization and Analysis of Large Transformer Model Training At-Scale. SIGMETRICS/Performance (Abstracts) 2024: 39-40 - [c32]Zhen Xie, Murali Emani, Xiaodong Yu, Dingwen Tao, Xin He, Pengfei Su, Keren Zhou, Venkatram Vishwanath:
Centimani: Enabling Fast AI Accelerator Selection for DNN Training with a Novel Performance Predictor. USENIX ATC 2024: 1203-1221 - [i14]Wes Brewer, Ana Gainaru, Frédéric Suter, Feiyi Wang, Murali Emani, Shantenu Jha
AI-coupled HPC Workflow Applications, Middleware and Performance. CoRR abs/2406.14315 (2024) - 2023
- [j9]Krishna Teja Chitty-Venkata
Neural Architecture Search Benchmarks: Insights and Survey. IEEE Access 11: 25217-25236 (2023) - [j8]Krishna Teja Chitty-Venkata
Differentiable Neural Architecture, Mixed Precision and Accelerator Co-Search. IEEE Access 11: 106670-106687 (2023) - [j7]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
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. Int. J. High Perform. Comput. Appl. 37(6): 683-705 (2023) - [j6]Krishna Teja Chitty-Venkata, Sparsh Mittal
A survey of techniques for optimizing transformer inference. J. Syst. Archit. 144: 102990 (2023) - [c31]Zhen Xie, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath:
TrainBF: High-Performance DNN Training Engine Using BFloat16 on AI Accelerators. Euro-Par 2023: 458-473 - [c30]Le Chen
LM4HPC: Towards Effective Language Model Application in High-Performance Computing. IWOMP 2023: 18-33 - [c29]Gaurav Verma
Transfer Learning Across Heterogeneous Features For Efficient Tensor Program Generation. ExHET@PPoPP 2023: 2:1-2:6 - [c28]Le Chen
Data Race Detection Using Large Language Models. SC Workshops 2023: 215-223 - [c27]Xianzhong Ding
HPC-GPT: Integrating Large Language Model for High-Performance Computing. SC Workshops 2023: 951-960 - [c26]Reet Barik
Characterizing the Performance of Triangle Counting on Graphcore's IPU Architecture. SC Workshops 2023: 1949-1957 - [i13]Gaurav Verma, Siddhisanket Raskar, Zhen Xie, Abid M. Malik, Murali Emani, Barbara M. Chapman:
Transfer Learning Across Heterogeneous Features For Efficient Tensor Program Generation. CoRR abs/2304.05430 (2023) - [i12]Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma:
A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems. CoRR abs/2306.09457 (2023) - [i11]Le Chen, Pei-Hung Lin, Tristan Vanderbruggen, Chunhua Liao, Murali Emani, Bronis R. de Supinski:
LM4HPC: Towards Effective Language Model Application in High-Performance Computing. CoRR abs/2306.14979 (2023) - [i10]Krishna Teja Chitty-Venkata, Sparsh Mittal, Murali Emani, Venkatram Vishwanath, Arun K. Somani:
A Survey of Techniques for Optimizing Transformer Inference. CoRR abs/2307.07982 (2023) - [i9]Le Chen, Xianzhong Ding, Murali Emani, Tristan Vanderbruggen, Pei-Hung Lin, Chunhua Liao:
Data Race Detection Using Large Language Models. CoRR abs/2308.07505 (2023) - [i8]Murali Emani, Sam Foreman, Varuni Sastry, Zhen Xie, Siddhisanket Raskar, William Arnold, Rajeev Thakur, Venkatram Vishwanath, Michael E. Papka:
A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators. CoRR abs/2310.04607 (2023) - [i7]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
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR abs/2310.04610 (2023) - [i6]Xianzhong Ding, Le Chen, Murali Emani, Chunhua Liao, Pei-Hung Lin, Tristan Vanderbruggen, Zhen Xie, Alberto E. Cerpa, Wan Du:
HPC-GPT: Integrating Large Language Model for High-Performance Computing. CoRR abs/2311.12833 (2023) - 2022
- [j5]Hailu Xu
XUnified: A Framework for Guiding Optimal Use of GPU Unified Memory. IEEE Access 10: 82614-82625 (2022) - [j4]Krishna Teja Chitty-Venkata
Neural Architecture Search for Transformers: A Survey. IEEE Access 10: 108374-108412 (2022) - [j3]Anda Trifan, Defne Gorgun, Michael Salim, Zongyi Li
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. 36(5-6): 603-623 (2022) - [c25]Shilpika, Bethany Lusch
Toward an In-Depth Analysis of Multifidelity High Performance Computing Systems. CCGRID 2022: 716-725 - [c24]Gaurav Verma
Towards neural architecture-aware exploration of compiler optimizations in a deep learning {graph} compiler. CF 2022: 244-250 - [c23]Winson Chen, Tristan Vanderbruggen, Pei-Hung Lin, Chunhua Liao, Murali Emani:
Early Experience with Transformer-Based Similarity Analysis for DataRaceBench. Correctness@SC 2022: 45-53 - [c22]Patrick J. Flynn, Tristan Vanderbruggen, Chunhua Liao, Pei-Hung Lin, Murali Emani, Xipeng Shen:
Finding Reusable Machine Learning Components to Build Programming Language Processing Pipelines. ECSA (Tracks and Workshops) 2022: 402-417 - [c21]Krishna Teja Chitty-Venkata
Efficient Design Space Exploration for Sparse Mixed Precision Neural Architectures. HPDC 2022: 265-276 - [c20]Zifan Nan, Mithil Dave, Xipeng Shen
Interactive NLU-Powered Ontology-Based Workflow Synthesis for FAIR Support of HPC. HUST@SC 2022: 29-40 - [c19]Zhen Xie, Siddhisanket Raskar, Murali Emani:
Throughput-oriented and Accuracy-aware DNN Training with BFloat16 on GPU. IPDPS Workshops 2022: 1084-1087 - [c18]Murali Emani, Zhen Xie, Siddhisanket Raskar, Varuni Sastry, William Arnold, Bruce Wilson, Rajeev Thakur
A Comprehensive Evaluation of Novel AI Accelerators for Deep Learning Workloads. PMBS@SC 2022: 13-25 - [c17]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:
AI Benchmarking for Science: Efforts from the MLCommons Science Working Group. ISC Workshops 2022: 47-64 - [c16]Pei-Hung Lin, Chunhua Liao, Winson Chen, Tristan Vanderbruggen, Murali Emani, Hailu Xu:
Making Machine Learning Datasets and Models FAIR for HPC: A Methodology and Case Study. TransAI 2022: 128-134 - [i5]Patrick J. Flynn, Tristan Vanderbruggen, Chunhua Liao, Pei-Hung Lin, Murali Emani, Xipeng Shen:
Finding Reusable Machine Learning Components to Build Programming Language Processing Pipelines. CoRR abs/2208.05596 (2022) - [i4]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
FAIR for AI: An interdisciplinary, international, inclusive, and diverse community building perspective. CoRR abs/2210.08973 (2022) - [i3]Pei-Hung Lin, Chunhua Liao, Winson Chen, Tristan Vanderbruggen, Murali Emani, Hailu Xu:
Making Machine Learning Datasets and Models FAIR for HPC: A Methodology and Case Study. CoRR abs/2211.02092 (2022) - [i2]Sixing Yu, Murali Emani, Chunhua Liao, Pei-Hung Lin, Tristan Vanderbruggen, Xipeng Shen, Ali Jannesari:
Towards Seamless Management of AI Models in High-Performance Computing. CoRR abs/2212.06352 (2022) - 2021
- [j2]Murali Emani
Accelerating Scientific Applications With SambaNova Reconfigurable Dataflow Architecture. Comput. Sci. Eng. 23(2): 114-119 (2021) - [c15]Steven Farrell
MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. MLHPC@SC 2021: 33-45 - [c14]Gaurav Verma
HPCFAIR: Enabling FAIR AI for HPC Applications. MLHPC@SC 2021: 58-68 - [c13]Chunhua Liao
HPC Ontology: Towards a Unified Ontology for Managing Training Datasets and AI Models for High-Performance Computing. MLHPC@SC 2021: 69-80 - [c12]Alexander Brace, Michael Salim, Vishal Subbiah, Heng Ma, Murali Emani, Anda Trifan, Austin R. Clyde, Corey Adams, Thomas D. Uram, Hyun Seung Yoo
Stream-AI-MD: streaming AI-driven adaptive molecular simulations for heterogeneous computing platforms. PASC 2021: 6:1-6:13 - [i1]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:
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. CoRR abs/2110.11466 (2021) - 2020
- [j1]Sourav Chakraborty, Ignacio Laguna
EReinit: Scalable and efficient fault-tolerance for bulk-synchronous MPI applications. Concurr. Comput. Pract. Exp. 32(3) (2020)
2010 – 2019
- 2019
- [c11]Shilpika, Bethany Lusch
MELA: A Visual Analytics Tool for Studying Multifidelity HPC System Logs. DAAC@SC 2019: 13-18 - [c10]Hailu Xu
Machine Learning Guided Optimal Use of GPU Unified Memory. MCHPC@SC 2019: 64-70 - 2018
- [c9]Jayaraman J. Thiagarajan, Nikhil Jain, Rushil Anirudh, Alfredo Giménez, Rahul Sridhar, Aniruddha Marathe
Bootstrapping Parameter Space Exploration for Fast Tuning. ICS 2018: 385-395 - [c8]Nawrin Sultana, Anthony Skjellum, Ignacio Laguna, Matthew Shane Farmer, Kathryn M. Mohror, Murali Emani:
MPI Stages: Checkpointing MPI State for Bulk Synchronous Applications. EuroMPI 2018: 13:1-13:11 - [c7]Larisa Stoltzfus, Murali Emani, Pei-Hung Lin
Data Placement Optimization in GPU Memory Hierarchy using Predictive Modeling. MCHPC@SC 2018: 45-49 - [c6]Md Abdullah Shahneous Bari, Larisa Stoltzfus, Pei-Hung Lin
Is Data Placement Optimization Still Relevant on Newer GPUs? PMBS@SC 2018: 83-96 - 2016
- [c5]Bruno Bodin
Integrating Algorithmic Parameters into Benchmarking and Design Space Exploration in 3D Scene Understanding. PACT 2016: 57-69 - [c4]Murali Krishna Emani:
Mapping Medley: Adaptive Parallelism Mapping with Varying Optimization Goals. LCPC 2016: 299-313 - 2015
- [b1]Murali Krishna Emani:
Adaptive parallelism mapping in dynamic environments using machine learning. University of Edinburgh, UK, 2015 - [c3]Murali Krishna Emani, Michael F. P. O'Boyle:
Celebrating diversity: a mixture of experts approach for runtime mapping in dynamic environments. PLDI 2015: 499-508 - 2014
- [c2]Murali Krishna Emani, Michael F. P. O'Boyle:
Change Detection Based Parallelism Mapping: Exploiting Offline Models and Online Adaptation. LCPC 2014: 208-223 - 2013
- [c1]Murali Krishna Emani, Zheng Wang
Smart, adaptive mapping of parallelism in the presence of external workload. CGO 2013: 13:1-13:10
Coauthor Index
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last updated on 2024-10-23 21:22 CEST by the dblp team
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