Sanchari Sen

According to our database, Sanchari Sen authored at least 21 papers between 2017 and 2024.

Collaborative distances:

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

2024

14.1 A Software-Assisted Peak Current Regulation Scheme to Improve Power-Limited Inference Performance in a 5nm AI SoC.

Monodeep Kar, Joel Silberman, Swagath Venkataramani, Viji Srinivasan, Bruce M. Fleischer, Joshua Rubin, JohnDavid Lancaster, Sae Kyu Lee, Matthew Cohen, Matthew M. Ziegler, Nianzheng Cao, Sandra Woodward, Ankur Agrawal, Ching Zhou, Prasanth Chatarasi, Thomas Gooding, Michael Guillorn, Bahman Hekmatshoartabari, Philip Jacob, Radhika Jain, Shubham Jain, Jinwook Jung, Kyu-Hyoun Kim, Siyu Koswatta, Martin Lutz, Alberto Mannari, Abey Mathew, Indira Nair, Ashish Ranjan, Zhibin Ren, Scot Rider, Thomas Roewer, David L. Satterfield, Marcel Schaal, Sanchari Sen, Gustavo Tellez, Hung Tran, Wei Wang, Vidhi Zalani, Jintao Zhang, Xin Zhang, Vinay Shah, Robert M. Senger, Arvind Kumar, Pong-Fei Lu, Leland Chang

Proceedings of the IEEE International Solid-State Circuits Conference, 2024

2022

Deep Compression of Pre-trained Transformer Models.

Naigang Wang, Chi-Chun (Charlie) Liu, Swagath Venkataramani, Sanchari Sen, Chia-Yu Chen, Kaoutar El Maghraoui, Vijayalakshmi Srinivasan, Leland Chang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Layerwise Disaggregated Evaluation of Spiking Neural Networks.

Abinand Nallathambi, Sanchari Sen, Anand Raghunathan, Nitin Chandrachoodan

Proceedings of the ISLPED '22: ACM/IEEE International Symposium on Low Power Electronics and Design, Boston, MA, USA, August 1, 2022

AxFormer: Accuracy-driven Approximation of Transformers for Faster, Smaller and more Accurate NLP Models.

Amrit Nagarajan, Sanchari Sen, Jacob R. Stevens, Anand Raghunathan

Proceedings of the International Joint Conference on Neural Networks, 2022

Seprox: Sequence-Based Approximations for Compressing Ultra-Low Precision Deep Neural Networks.

Aradhana Mohan Parvathy, Sarada Krithivasan, Sanchari Sen, Anand Raghunathan

Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, 2022

Efficiency attacks on spiking neural networks.

Sarada Krithivasan, Sanchari Sen, Nitin Rathi, Kaushik Roy, Anand Raghunathan

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

2021

Quantifying the Brain Predictivity of Artificial Neural Networks With Nonlinear Response Mapping.

Aditi Anand, Sanchari Sen, Kaushik Roy

Frontiers Comput. Neurosci., 2021

Efficacy of Pruning in Ultra-Low Precision DNNs.

Sanchari Sen, Swagath Venkataramani, Anand Raghunathan

Proceedings of the IEEE/ACM International Symposium on Low Power Electronics and Design, 2021

RaPiD: AI Accelerator for Ultra-low Precision Training and Inference.

Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Wang, Sanchari Sen, Jintao Zhang, Ankur Agrawal, Monodeep Kar, Shubham Jain, Alberto Mannari, Hoang Tran, Yulong Li, Eri Ogawa, Kazuaki Ishizaki, Hiroshi Inoue, Marcel Schaal, Mauricio J. Serrano, Jungwook Choi, Xiao Sun, Naigang Wang, Chia-Yu Chen, Allison Allain, James Bonanno, Nianzheng Cao, Robert Casatuta, Matthew Cohen, Bruce M. Fleischer, Michael Guillorn, Howard Haynie, Jinwook Jung, Mingu Kang, Kyu-Hyoun Kim, Siyu Koswatta, Sae Kyu Lee, Martin Lutz, Silvia M. Mueller, Jinwook Oh, Ashish Ranjan, Zhibin Ren, Scot Rider, Kerstin Schelm, Michael Scheuermann, Joel Silberman, Jie Yang, Vidhi Zalani, Xin Zhang, Ching Zhou, Matthew M. Ziegler, Vinay Shah, Moriyoshi Ohara, Pong-Fei Lu, Brian W. Curran, Sunil Shukla, Leland Chang, Kailash Gopalakrishnan

Proceedings of the 48th ACM/IEEE Annual International Symposium on Computer Architecture, 2021

Value Similarity Extensions for Approximate Computing in General-Purpose Processors.

Younghoon Kim, Swagath Venkataramani, Sanchari Sen, Anand Raghunathan

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

2020

Sparsity Turns Adversarial: Energy and Latency Attacks on Deep Neural Networks.

Sarada Krithivasan, Sanchari Sen, Anand Raghunathan

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020

Optimizing Transformers with Approximate Computing for Faster, Smaller and more Accurate NLP Models.

Amrit Nagarajan, Sanchari Sen, Jacob R. Stevens, Anand Raghunathan

CoRR, 2020

Adversarial Sparsity Attacks on Deep Neural Networks.

Sarada Krithivasan, Sanchari Sen, Anand Raghunathan

CoRR, 2020

A Case for Generalizable DNN Cost Models for Mobile Devices.

Vinod Ganesan, Surya Selvam, Sanchari Sen, Pratyush Kumar, Anand Raghunathan

Proceedings of the IEEE International Symposium on Workload Characterization, 2020

EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness Against Adversarial Attacks.

Sanchari Sen, Balaraman Ravindran, Anand Raghunathan

Proceedings of the 8th International Conference on Learning Representations, 2020

Sparsity-Aware Caches to Accelerate Deep Neural Networks.

Vinod Ganesan, Sanchari Sen, Pratyush Kumar, Neel Gala, Kamakoti Veezhinathan, Anand Raghunathan

Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

2019

SparCE: Sparsity Aware General-Purpose Core Extensions to Accelerate Deep Neural Networks.

Sanchari Sen, Shubham Jain, Swagath Venkataramani, Anand Raghunathan

IEEE Trans. Computers, 2019

Dynamic Spike Bundling for Energy-Efficient Spiking Neural Networks.

Sarada Krithivasan, Sanchari Sen, Swagath Venkataramani, Anand Raghunathan

Proceedings of the 2019 IEEE/ACM International Symposium on Low Power Electronics and Design, 2019

2018

Approximate Computing for Long Short Term Memory (LSTM) Neural Networks.

Sanchari Sen, Anand Raghunathan

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2018

2017

A Programmable Event-driven Architecture for Evaluating Spiking Neural Networks.

Arnab Roy, Swagath Venkataramani, Neel Gala, Sanchari Sen, Kamakoti Veezhinathan, Anand Raghunathan

Proceedings of the 2017 IEEE/ACM International Symposium on Low Power Electronics and Design, 2017

Approximate computing for spiking neural networks.

Sanchari Sen, Swagath Venkataramani, Anand Raghunathan

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2017