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ORCIDSanchari Sen
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2020 – today
- 2024
[c15]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:
14.1 A Software-Assisted Peak Current Regulation Scheme to Improve Power-Limited Inference Performance in a 5nm AI SoC. ISSCC 2024: 254-256- [i5]Rui Xie, Asad Ul Haq, Linsen Ma, Krystal Sun, Sanchari Sen, Swagath Venkataramani, Liu Liu, Tong Zhang:
SmartQuant: CXL-based AI Model Store in Support of Runtime Configurable Weight Quantization. CoRR abs/2407.15866 (2024) - 2022
- [c14]Sarada Krithivasan, Sanchari Sen, Nitin Rathi, Kaushik Roy, Anand Raghunathan:
Efficiency attacks on spiking neural networks. DAC 2022: 373-378 - [c13]Aradhana Mohan Parvathy, Sarada Krithivasan, Sanchari Sen, Anand Raghunathan:
Seprox: Sequence-Based Approximations for Compressing Ultra-Low Precision Deep Neural Networks. ICCAD 2022: 153:1-153:9 - [c12]Amrit Nagarajan, Sanchari Sen, Jacob R. Stevens, Anand Raghunathan:
AxFormer: Accuracy-driven Approximation of Transformers for Faster, Smaller and more Accurate NLP Models. IJCNN 2022: 1-8 - [c11]Abinand Nallathambi, Sanchari Sen, Anand Raghunathan, Nitin Chandrachoodan:
Layerwise Disaggregated Evaluation of Spiking Neural Networks. ISLPED 2022: 25:1-25:6 - [c10]Naigang Wang, Chi-Chun (Charlie) Liu, Swagath Venkataramani, Sanchari Sen, Chia-Yu Chen, Kaoutar El Maghraoui, Vijayalakshmi Srinivasan, Leland Chang:
Deep Compression of Pre-trained Transformer Models. NeurIPS 2022 - 2021
- [j4]Aditi Anand, Sanchari Sen, Kaushik Roy:
Quantifying the Brain Predictivity of Artificial Neural Networks With Nonlinear Response Mapping. Frontiers Comput. Neurosci. 15: 609721 (2021) - [c9]Younghoon Kim, Swagath Venkataramani, Sanchari Sen, Anand Raghunathan:
Value Similarity Extensions for Approximate Computing in General-Purpose Processors. DATE 2021: 481-486 - [c8]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:
RaPiD: AI Accelerator for Ultra-low Precision Training and Inference. ISCA 2021: 153-166 - [c7]Sanchari Sen, Swagath Venkataramani, Anand Raghunathan:
Efficacy of Pruning in Ultra-Low Precision DNNs. ISLPED 2021: 1-6 - 2020
- [j3]Sarada Krithivasan, Sanchari Sen, Anand Raghunathan:
Sparsity Turns Adversarial: Energy and Latency Attacks on Deep Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(11): 4129-4141 (2020) - [c6]Vinod Ganesan, Sanchari Sen, Pratyush Kumar, Neel Gala, Kamakoti Veezhinathan, Anand Raghunathan:
Sparsity-Aware Caches to Accelerate Deep Neural Networks. DATE 2020: 85-90 - [c5]Sanchari Sen, Balaraman Ravindran, Anand Raghunathan:
EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness Against Adversarial Attacks. ICLR 2020 - [c4]Vinod Ganesan, Surya Selvam, Sanchari Sen, Pratyush Kumar, Anand Raghunathan:
A Case for Generalizable DNN Cost Models for Mobile Devices. IISWC 2020: 169-180 - [i4]Sanchari Sen, Balaraman Ravindran, Anand Raghunathan:
EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness against Adversarial Attacks. CoRR abs/2004.10162 (2020) - [i3]Sarada Krithivasan, Sanchari Sen, Anand Raghunathan:
Adversarial Sparsity Attacks on Deep Neural Networks. CoRR abs/2006.08020 (2020) - [i2]Amrit Nagarajan, Sanchari Sen, Jacob R. Stevens, Anand Raghunathan:
Optimizing Transformers with Approximate Computing for Faster, Smaller and more Accurate NLP Models. CoRR abs/2010.03688 (2020)
2010 – 2019
- 2019
- [j2]Sanchari Sen, Shubham Jain, Swagath Venkataramani, Anand Raghunathan:
SparCE: Sparsity Aware General-Purpose Core Extensions to Accelerate Deep Neural Networks. IEEE Trans. Computers 68(6): 912-925 (2019) - [c3]Sarada Krithivasan, Sanchari Sen, Swagath Venkataramani, Anand Raghunathan:
Dynamic Spike Bundling for Energy-Efficient Spiking Neural Networks. ISLPED 2019: 1-6 - 2018
- [j1]Sanchari Sen, Anand Raghunathan:
Approximate Computing for Long Short Term Memory (LSTM) Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37(11): 2266-2276 (2018) - 2017
- [c2]Sanchari Sen, Swagath Venkataramani, Anand Raghunathan:
Approximate computing for spiking neural networks. DATE 2017: 193-198 - [c1]Arnab Roy, Swagath Venkataramani, Neel Gala, Sanchari Sen, Kamakoti Veezhinathan, Anand Raghunathan:
A Programmable Event-driven Architecture for Evaluating Spiking Neural Networks. ISLPED 2017: 1-6 - [i1]Sanchari Sen, Shubham Jain, Swagath Venkataramani, Anand Raghunathan:
SparCE: Sparsity aware General Purpose Core Extensions to Accelerate Deep Neural Networks. CoRR abs/1711.06315 (2017)
Coauthor Index
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