Murali Emani
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
25
Venues
12
Active years
2018–2026
Best venue rank
A*
Where they publish
Papers
25 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 | ICCV | MoPEQ: Mixture of Mixed Precision Quantized Experts. | Krishna Teja Chitty-Venkata, Jie Ye, Murali Emani |
| 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 | 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 | Enabling Unstructured Sparse Fine-Tuning and Inference for Foundation Models on Wafer-Scale Engine. | Haoyu Zheng, Yifan Zeng, Linghao Song, Murali Emani, Wenqian Dong |
| 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 | 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 | 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 | PPoPP | Transfer Learning Across Heterogeneous Features For Efficient Tensor Program Generation. | Gaurav Verma, Siddhisanket Raskar, Zhen Xie, Abid M. Malik, Murali Emani, Barbara M. Chapman |
| 2023 | SC | Characterizing the Performance of Triangle Counting on Graphcore's IPU Architecture. | Reet Barik, Siddhisanket Raskar, Murali Emani, Venkatram Vishwanath |
| 2023 | SC | Data Race Detection Using Large Language Models. | Le Chen, Xianzhong Ding, Murali Emani, Tristan Vanderbruggen, Pei-Hung Lin, Chunhua Liao |
| 2023 | SC | 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 |
| 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 | ECSA | 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 |
| 2022 | HPDC | Efficient Design Space Exploration for Sparse Mixed Precision Neural Architectures. | Krishna Teja Chitty-Venkata, Murali Emani, Venkatram Vishwanath, Arun K. Somani |
| 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 |
| 2019 | SC | Machine Learning Guided Optimal Use of GPU Unified Memory. | Hailu Xu, Murali Emani, Pei-Hung Lin, Liting Hu, Chunhua Liao |
| 2018 | ICS | Bootstrapping Parameter Space Exploration for Fast Tuning. | Jayaraman J. Thiagarajan, Nikhil Jain, Rushil Anirudh, Alfredo Gimnez, Rahul Sridhar, Aniruddha Marathe, Tao Wang, Murali Emani, Abhinav Bhatele, Todd Gamblin |
| 2018 | SC | 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 |
| 2018 | SC | Data Placement Optimization in GPU Memory Hierarchy using Predictive Modeling. | Larisa Stoltzfus, Murali Emani, Pei-Hung Lin, Chunhua Liao |