Animesh Jain

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 20

Top Topics

Efficient Execution

Iterative Optimization

Top Venues

Publications

Jason Ansel, Edward Z. Yang, Horace He, Natalia Gimelshein, Animesh Jain, Michael Voznesensky, Bin Bao, Peter Bell, David Berard, Evgeni Burovski, Geeta Chauhan, Anjali Chourdia, Will Constable, Alban Desmaison, Zachary DeVito, Elias Ellison, Will Feng, Jiong Gong, Michael Gschwind, Brian Hirsh, Sherlock Huang, Kshiteej Kalambarkar, Laurent Kirsch, Michael Lazos, Mario Lezcano, Yanbo Liang, Jason Liang, Yinghai Lu, C. K. Luk, Bert Maher, Yunjie Pan, Christian Puhrsch, Matthias Reso, Mark Saroufim, Marcos Yukio Siraichi, Helen Suk, Shunting Zhang, Michael Suo, Phil Tillet, Xu Zhao, Eikan Wang, Keren Zhou, Richard Zou, Xiaodong Wang, Ajit Mathews, William Wen, Gregory Chanan, Peng Wu, Soumith Chintala
PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation. ASPLOS (2) (2024)
Kaiqi Zhao, Animesh Jain, Ming Zhao
Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions. CoRR (2023)
Sanket Purandare, Abdul Wasay, Animesh Jain, Stratos Idreos
μ-TWO: 3× Faster Multi-Model Training with Orchestration and Memory Optimization. MLSys (2023)
Yogesh K. Dwivedi, Nir Kshetri, Laurie Hughes, Nripendra P. Rana, Abdullah M. Baabdullah, Arpan Kumar Kar, Alex Koohang, Samuel Ribeiro-Navarrete, Nina Belei, Janarthanan Balakrishnan, Sriparna Basu, Abhishek Behl, Gareth H. Davies, Vincent Dutot, Rohita Dwivedi, Leighton Evans, Reto Felix, Richard Foster-Fletcher, Mihalis Giannakis, Ashish Gupta, Chris Hinsch, Animesh Jain, Nina Jane Patel, Timothy Jung, Satinder Juneja, Qeis Kamran, Sanjar Mohamed AB, Neeraj Pandey, Savvas Papagiannidis, Ramakrishnan Raman, Philipp A. Rauschnabel, Preeti Tak, Alexandra Taylor, M. Claudia tom Dieck, Giampaolo Viglia, Yichuan Wang, Meiyi Yan
Exploring the Darkverse: A Multi-Perspective Analysis of the Negative Societal Impacts of the Metaverse. Inf. Syst. Frontiers 25 (5) (2023)
Kaiqi Zhao, Animesh Jain, Ming Zhao
Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions. AISTATS (2023)
Krishnan Sukumar, Santosh Vodnala, Ravindra Ayyagari, Animesh Jain, Thanapandi Ganesan, Rajesh R
Surmounting Challenges in the Design of Low Power Real Time Clock IP for Advanced FinFET Technology Nodes. VLSID (2023)
Kaiqi Zhao, Animesh Jain, Ming Zhao
Iterative Activation-based Structured Pruning. CoRR (2022)
Kaiqi Zhao, Animesh Jain, Ming Zhao
Adaptive Activation-based Structured Pruning. CoRR (2022)
Kaiqi Zhao, Hieu Nguyen, Animesh Jain, Nathan Susanj, Athanasios Mouchtaris, Lokesh Gupta, Ming Zhao
Knowledge Distillation via Module Replacing for Automatic Speech Recognition with Recurrent Neural Network Transducer. INTERSPEECH (2022)
Ziheng Jiang, Animesh Jain, Andrew Liu, Josh Fromm, Chengqian Ma, Tianqi Chen, Luis Ceze
Automated Backend-Aware Post-Training Quantization. CoRR (2021)
Jian Weng, Animesh Jain, Jie Wang, Leyuan Wang, Yida Wang, Tony Nowatzki
UNIT: Unifying Tensorized Instruction Compilation. CGO (2021)
Jian Weng, Animesh Jain, Jie Wang, Leyuan Wang, Yida Wang, Tony Nowatzki
UNIT: Unifying Tensorized Instruction Compilation. CoRR (2021)
Hongbin Zheng, Sejong Oh, Huiqing Wang, Preston Briggs, Jiading Gai, Animesh Jain, Yizhi Liu, Rich Heaton, Randy Huang, Yida Wang
Optimizing Memory-Access Patterns for Deep Learning Accelerators. CoRR (2020)
Animesh Jain, Shoubhik Bhattacharya, Masahiro Masuda, Vin Sharma, Yida Wang
Efficient Execution of Quantized Deep Learning Models: A Compiler Approach. CoRR (2020)
Animesh Jain, Michael A. Laurenzano, Gilles A. Pokam, Jason Mars, Lingjia Tang
Architectural support for convolutional neural networks on modern CPUs. PACT (2018)
Animesh Jain, Amar Phanishayee, Jason Mars, Lingjia Tang, Gennady Pekhimenko
Gist: Efficient Data Encoding for Deep Neural Network Training. ISCA (2018)
Ram Srivatsa Kannan, Animesh Jain, Michael A. Laurenzano, Lingjia Tang, Jason Mars
Proctor: Detecting and Investigating Interference in Shared Datacenters. ISPASS (2018)
Parker Hill, Animesh Jain, Mason Hill, Babak Zamirai, Chang-Hong Hsu, Michael A. Laurenzano, Scott A. Mahlke, Lingjia Tang, Jason Mars
DeftNN: addressing bottlenecks for DNN execution on GPUs via synapse vector elimination and near-compute data fission. MICRO (2017)
Animesh Jain, Parker Hill, Shih-Chieh Lin, Muneeb Khan, Md. Enamul Haque, Michael A. Laurenzano, Scott A. Mahlke, Lingjia Tang, Jason Mars
Concise loads and stores: The case for an asymmetric compute-memory architecture for approximation. MICRO (2016)
Animesh Jain, Michael A. Laurenzano, Lingjia Tang, Jason Mars
Continuous shape shifting: Enabling loop co-optimization via near-free dynamic code rewriting. MICRO (2016)
Animesh Jain, Ritesh Parikh, Valeria Bertacco
High-radix on-chip networks with low-radix routers. ICCAD (2014)