Swagath Venkataramani

101 papers A* 19A 27B 2C 1Misc 4Journal 34Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	A	`conf`	Eliminating Redundancy: Ultra-compact Code Generation for Programmable Dataflow Accelerators. CGO Prasanth Chatarasi, Alex Gatea, Bardia Mahjour, Jintao Zhang, Alberto Mannari, Chris Bowler, Shubham Jain, Masoud Ataei Jaliseh, Nicole Khoun, Kamlesh Kumar, Viji Srinivasan, Swagath Venkataramani
2026	A	`conf`	Enabling Spill-Free Compilation via Affine-Based Live Range Reduction Optimization. CGO Prasanth Chatarasi, Alex Gatea, Wei Wang, Chris Bowler, Shubham Jain, Masoud Ataei Jaliseh, Nicole Khoun, Alberto Mannari, Bardia Mahjour, Viji Srinivasan, Swagath Venkataramani
2026	J	`jnl`	Is Finer Better? The Limits of Microscaling Formats in Large Language Models. CoRR Andrea Fasoli, Monodeep Kar, Chi-Chun (Charlie) Liu, Swagath Venkataramani, Viji Srinivasan, Leland Chang, Naigang Wang
2026	—	`conf`	Spyre: An Inference-Optimized Scalable AI Accelerator for Enterprise Workloads. ISSCC Matthew Cohen, Monodeep Kar, Swagath Venkataramani, Viji Srinivasan, Brian Veraa, Matthew M. Ziegler, Nianzheng Cao, Ashish Ranjan, Joel Silberman, Michael Guillorn, Sandra Woodward, JohnDavid Lancaster, Josh Hursey, Kyu-Hyoun Kim, Alberto Mannari, Amrit Nagarajan, Ananda Samajdar, Bahman Hekmatshoartabari, Bob Galbraith, Ching Zhou, David L. Satterfield, Gregory S. Still, Gustavo Tellez, Indira Nair, Indu Masilamanai, Jinwook Jung, Kavi Randhawa, Marcel Schaal, Martin Lutz, Paul Crumley, Philip Jacob, Prasanth Chatarasi, Radhika Jain, Sae Kyu Lee, Sanchari Sen, Sarada Krithivasan, Scot Rider, Shubham Jain, Siyu Koswatta, Thomas Roewer, Tom Gooding, Victor Ferrari, Vidhi Zalani, Zhibin Ren, Kevin Reick, Lisa Maurice, Christopher J. Gonzalez, Chris Catalino, Ryan Nett, Pong-Fei Lu, Robert M. Senger, Leland Chang
2025	J	`jnl`	Breaking the HBM Bit Cost Barrier: Domain-Specific ECC for AI Inference Infrastructure. IEEE Comput. Archit. Lett. Rui Xie, Asad Ul Haq, Yunhua Fang, Linsen Ma, Sanchari Sen, Swagath Venkataramani, Liu Liu, Tong Zhang
2025	J	`jnl`	Breaking the HBM Bit Cost Barrier: Domain-Specific ECC for AI Inference Infrastructure. CoRR Rui Xie, Asad Ul Haq, Yunhua Fang, Linsen Ma, Sanchari Sen, Swagath Venkataramani, Liu Liu, Tong Zhang
2025	J	`jnl`	Making Strong Error-Correcting Codes Work Effectively for HBM in AI Inference. CoRR Rui Xie, Yunhua Fang, Asad Ul Haq, Linsen Ma, Sanchari Sen, Swagath Venkataramani, Liu Liu, Tong Zhang
2025	J	`jnl`	Power-Limited Inference Performance Optimization Using a Software-Assisted Peak Current Regulation Scheme in a 5-nm AI SoC. IEEE J. Solid State Circuits 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 Röwer, 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
2024	—	`conf`	14.1 A Software-Assisted Peak Current Regulation Scheme to Improve Power-Limited Inference Performance in a 5nm AI SoC. ISSCC 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
2024	J	`jnl`	DNNDaSher: A Compiler Framework for Dataflow Compatible End-to-End Acceleration on IBM AIU. IEEE Micro Sanchari Sen, Shubham Jain, Sarada Krithivasan, Swagath Venkataramani, Vijayalakshmi Srinivasan
2024	J	`jnl`	Enhance DNN Adversarial Robustness and Efficiency via Injecting Noise to Non-Essential Neurons. CoRR Zhenyu Liu, Garrett Gagnon, Swagath Venkataramani, Liu Liu
2024	J	`jnl`	MixTrain: accelerating DNN training via input mixing. Frontiers Artif. Intell. Sarada Krithivasan, Sanchari Sen, Swagath Venkataramani, Anand Raghunathan
2024	J	`jnl`	SmartQuant: CXL-Based AI Model Store in Support of Runtime Configurable Weight Quantization. IEEE Comput. Archit. Lett. Rui Xie, Asad Ul Haq, Linsen Ma, Krystal Sun, Sanchari Sen, Swagath Venkataramani, Liu Liu, Tong Zhang
2024	J	`jnl`	SmartQuant: CXL-based AI Model Store in Support of Runtime Configurable Weight Quantization. CoRR Rui Xie, Asad Ul Haq, Linsen Ma, Krystal Sun, Sanchari Sen, Swagath Venkataramani, Liu Liu, Tong Zhang
2022	J	`jnl`	A 7-nm Four-Core Mixed-Precision AI Chip With 26.2-TFLOPS Hybrid-FP8 Training, 104.9-TOPS INT4 Inference, and Workload-Aware Throttling. IEEE J. Solid State Circuits Sae Kyu Lee, Ankur Agrawal, Joel Silberman, Matthew M. Ziegler, Mingu Kang, Swagath Venkataramani, Nianzheng Cao, Bruce M. Fleischer, Michael Guillorn, Matthew Cohen, Silvia M. Mueller, Jinwook Oh, Martin Lutz, Jinwook Jung, Siyu Koswatta, Ching Zhou, Vidhi Zalani, Monodeep Kar, James Bonanno, Robert Casatuta, Chia-Yu Chen, Jungwook Choi, Howard Haynie, Alyssa Herbert, Radhika Jain, Kyu-Hyoun Kim, Yulong Li, Zhibin Ren, Scot Rider, Marcel Schaal, Kerstin Schelm, Michael Scheuermann, Xiao Sun, Hung Tran, Naigang Wang, Wei Wang, Xin Zhang, Vinay Shah, Brian W. Curran, Vijayalakshmi Srinivasan, Pong-Fei Lu, Sunil Shukla, Kailash Gopalakrishnan, Leland Chang
2022	A	`conf`	Accelerating Inference and Language Model Fusion of Recurrent Neural Network Transducers via End-to-End 4-bit Quantization. INTERSPEECH Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Kailash Gopalakrishnan
2022	J	`jnl`	Accelerating Inference and Language Model Fusion of Recurrent Neural Network Transducers via End-to-End 4-bit Quantization. CoRR Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Kailash Gopalakrishnan
2022	A	`conf`	Approximate Computing and the Efficient Machine Learning Expedition. ICCAD Jörg Henkel, Hai Li, Anand Raghunathan, Mehdi B. Tahoori, Swagath Venkataramani, Xiaoxuan Yang, Georgios Zervakis
2022	J	`jnl`	Approximate Computing and the Efficient Machine Learning Expedition. CoRR Jörg Henkel, Hai Li, Anand Raghunathan, Mehdi B. Tahoori, Swagath Venkataramani, Xiaoxuan Yang, Georgios Zervakis
2022	A*	`conf`	Deep Compression of Pre-trained Transformer Models. NeurIPS Naigang Wang, Chi-Chun (Charlie) Liu, Swagath Venkataramani, Sanchari Sen, Chia-Yu Chen, Kaoutar El Maghraoui, Vijayalakshmi Srinivasan, Leland Chang
2022	J	`jnl`	OnSRAM: Efficient Inter-Node On-Chip Scratchpad Management in Deep Learning Accelerators. ACM Trans. Embed. Comput. Syst. Subhankar Pal, Swagath Venkataramani, Viji Srinivasan, Kailash Gopalakrishnan
2021	A	`conf`	4-Bit Quantization of LSTM-Based Speech Recognition Models. Interspeech Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Xiao Sun, Naigang Wang, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Wei Zhang, Zoltán Tüske, Kailash Gopalakrishnan
2021	J	`jnl`	4-bit Quantization of LSTM-based Speech Recognition Models. CoRR Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Xiao Sun, Naigang Wang, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Wei Zhang, Zoltán Tüske, Kailash Gopalakrishnan
2021	—	`conf`	A 7nm 4-Core AI Chip with 25.6TFLOPS Hybrid FP8 Training, 102.4TOPS INT4 Inference and Workload-Aware Throttling. ISSCC Ankur Agrawal, Sae Kyu Lee, Joel Silberman, Matthew M. Ziegler, Mingu Kang, Swagath Venkataramani, Nianzheng Cao, Bruce M. Fleischer, Michael Guillorn, Matt Cohen, Silvia M. Mueller, Jinwook Oh, Martin Lutz, Jinwook Jung, Siyu Koswatta, Ching Zhou, Vidhi Zalani, James Bonanno, Robert Casatuta, Chia-Yu Chen, Jungwook Choi, Howard Haynie, Alyssa Herbert, Radhika Jain, Monodeep Kar, Kyu-Hyoun Kim, Yulong Li, Zhibin Ren, Scot Rider, Marcel Schaal, Kerstin Schelm, Michael Scheuermann, Xiao Sun, Hung Tran, Naigang Wang, Wei Wang, Xin Zhang, Vinay Shah, Brian W. Curran, Vijayalakshmi Srinivasan, Pong-Fei Lu, Sunil Shukla, Leland Chang, Kailash Gopalakrishnan
2021	A	`conf`	Efficacy of Pruning in Ultra-Low Precision DNNs. ISLPED Sanchari Sen, Swagath Venkataramani, Anand Raghunathan
2021	B	`conf`	Efficient Management of Scratch-Pad Memories in Deep Learning Accelerators. ISPASS Subhankar Pal, Swagath Venkataramani, Viji Srinivasan, Kailash Gopalakrishnan
2021	A*	`conf`	RaPiD: AI Accelerator for Ultra-low Precision Training and Inference. ISCA 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
2021	J	`jnl`	ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training. CoRR Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan
2021	A	`conf`	Value Similarity Extensions for Approximate Computing in General-Purpose Processors. DATE Younghoon Kim, Swagath Venkataramani, Sanchari Sen, Anand Raghunathan
2020	—	`conf`	A 3.0 TFLOPS 0.62V Scalable Processor Core for High Compute Utilization AI Training and Inference. VLSI Circuits Jinwook Oh, Sae Kyu Lee, Mingu Kang, Matthew M. Ziegler, Joel Silberman, Ankur Agrawal, Swagath Venkataramani, Bruce M. Fleischer, Michael Guillorn, Jungwook Choi, Wei Wang, Silvia M. Mueller, Shimon Ben-Yehuda, James Bonanno, Nianzheng Cao, Robert Casatuta, Chia-Yu Chen, Matt Cohen, Ophir Erez, Thomas W. Fox, George Gristede, Howard Haynie, Vicktoria Ivanov, Siyu Koswatta, Shih-Hsien Lo, Martin Lutz, Gary W. Maier, Alex Mesh, Yevgeny Nustov, Scot Rider, Marcel Schaal, Michael Scheuermann, Xiao Sun, Naigang Wang, Fanchieh Yee, Ching Zhou, Vinay Shah, Brian W. Curran, Vijayalakshmi Srinivasan, Pong-Fei Lu, Sunil Shukla, Kailash Gopalakrishnan, Leland Chang
2020	J	`jnl`	DyVEDeep: Dynamic Variable Effort Deep Neural Networks. ACM Trans. Embed. Comput. Syst. Sanjay Ganapathy, Swagath Venkataramani, Giridhur Sriraman, Balaraman Ravindran, Anand Raghunathan
2020	J	`jnl`	Efficient AI System Design With Cross-Layer Approximate Computing. Proc. IEEE Swagath Venkataramani, Xiao Sun, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Mingu Kang, Ankur Agarwal, Jinwook Oh, Shubham Jain, Tina Babinsky, Nianzheng Cao, Thomas W. Fox, Bruce M. Fleischer, George Gristede, Michael Guillorn, Howard Haynie, Hiroshi Inoue, Kazuaki Ishizaki, Michael J. Klaiber, Shih-Hsien Lo, Gary W. Maier, Silvia M. Mueller, Michael Scheuermann, Eri Ogawa, Marcel Schaal, Mauricio J. Serrano, Joel Silberman, Christos Vezyrtzis, Wei Wang, Fanchieh Yee, Jintao Zhang, Matthew M. Ziegler, Ching Zhou, Moriyoshi Ohara, Pong-Fei Lu, Brian W. Curran, Sunil Shukla, Vijayalakshmi Srinivasan, Leland Chang, Kailash Gopalakrishnan
2020	J	`jnl`	Logic Synthesis of Approximate Circuits. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Swagath Venkataramani, Vivek Joy Kozhikkottu, Amit Sabne, Kaushik Roy, Anand Raghunathan
2020	A*	`conf`	ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training. NeurIPS Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan
2020	A*	`conf`	Ultra-Low Precision 4-bit Training of Deep Neural Networks. NeurIPS Xiao Sun, Naigang Wang, Chia-Yu Chen, Jiamin Ni, Ankur Agrawal, Xiaodong Cui, Swagath Venkataramani, Kaoutar El Maghraoui, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan
2019	—	`conf`	A Compiler for Deep Neural Network Accelerators to Generate Optimized Code for a Wide Range of Data Parameters from a Hand-crafted Computation Kernel. COOL CHIPS Eri Ogawa, Kazuaki Ishizaki, Hiroshi Inoue, Swagath Venkataramani, Jungwook Choi, Wei Wang, Vijayalakshmi Srinivasan, Moriyoshi Ohara, Kailash Gopalakrishnan
2019	—	`conf`	Accurate and Efficient 2-bit Quantized Neural Networks. SysML Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan, Zhuo Wang, Pierce Chuang
2019	—	`ch.`	Approximate Computing Techniques for Deep Neural Networks. Approximate Circuits Jungwook Choi, Swagath Venkataramani
2019	—	`ch.`	Automatic Synthesis Techniques for Approximate Circuits. Approximate Circuits Ashish Ranjan, Swagath Venkataramani, Shubham Jain, Younghoon Kim, Shankar Ganesh Ramasubramanian, Arnab Raha, Kaushik Roy, Anand Raghunathan
2019	A*	`conf`	BiScaled-DNN: Quantizing Long-tailed Datastructures with Two Scale Factors for Deep Neural Networks. DAC Shubham Jain, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang
2019	A	`conf`	Data Subsetting: A Data-Centric Approach to Approximate Computing. DATE Younghoon Kim, Swagath Venkataramani, Nitin Chandrachoodan, Anand Raghunathan
2019	J	`jnl`	DeepTools: Compiler and Execution Runtime Extensions for RaPiD AI Accelerator. IEEE Micro Swagath Venkataramani, Jungwook Choi, Vijayalakshmi Srinivasan, Wei Wang, Jintao Zhang, Marcel Schaal, Mauricio J. Serrano, Kazuaki Ishizaki, Hiroshi Inoue, Eri Ogawa, Moriyoshi Ohara, Leland Chang, Kailash Gopalakrishnan
2019	A	`conf`	Dynamic Spike Bundling for Energy-Efficient Spiking Neural Networks. ISLPED Sarada Krithivasan, Sanchari Sen, Swagath Venkataramani, Anand Raghunathan
2019	A*	`conf`	Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks. NeurIPS Xiao Sun, Jungwook Choi, Chia-Yu Chen, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Xiaodong Cui, Wei Zhang, Kailash Gopalakrishnan
2019	Misc	`conf`	Memory and Interconnect Optimizations for Peta-Scale Deep Learning Systems. HiPC Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Philip Heidelberger, Leland Chang, Kailash Gopalakrishnan
2019	—	`conf`	Performance-driven Programming of Multi-TFLOP Deep Learning Accelerators. IISWC Swagath Venkataramani, Jungwook Choi, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan, Leland Chang
2019	J	`jnl`	SparCE: Sparsity Aware General-Purpose Core Extensions to Accelerate Deep Neural Networks. IEEE Trans. Computers Sanchari Sen, Shubham Jain, Swagath Venkataramani, Anand Raghunathan
2019	Misc	`conf`	Workload-aware Automatic Parallelization for Multi-GPU DNN Training. ICASSP Sungho Shin, Youngmin Jo, Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wonyong Sung
2018	—	`conf`	A Scalable Multi- TeraOPS Deep Learning Processor Core for AI Trainina and Inference. VLSI Circuits Bruce M. Fleischer, Sunil Shukla, Matthew M. Ziegler, Joel Silberman, Jinwook Oh, Vijayalakshmi Srinivasan, Jungwook Choi, Silvia M. Mueller, Ankur Agrawal, Tina Babinsky, Nianzheng Cao, Chia-Yu Chen, Pierce Chuang, Thomas W. Fox, George Gristede, Michael Guillorn, Howard Haynie, Michael J. Klaiber, Dongsoo Lee, Shih-Hsien Lo, Gary W. Maier, Michael Scheuermann, Swagath Venkataramani, Christos Vezyrtzis, Naigang Wang, Fanchieh Yee, Ching Zhou, Pong-Fei Lu, Brian W. Curran, Leland Chang, Kailash Gopalakrishnan
2018	A	`conf`	Across the Stack Opportunities for Deep Learning Acceleration. ISLPED Vijayalakshmi Srinivasan, Bruce M. Fleischer, Sunil Shukla, Matthew M. Ziegler, Joel Silberman, Jinwook Oh, Jungwook Choi, Silvia M. Mueller, Ankur Agrawal, Tina Babinsky, Nianzheng Cao, Chia-Yu Chen, Pierce Chuang, Thomas W. Fox, George Gristede, Michael Guillorn, Howard Haynie, Michael J. Klaiber, Dongsoo Lee, Shih-Hsien Lo, Gary W. Maier, Michael Scheuermann, Swagath Venkataramani, Christos Vezyrtzis, Naigang Wang, Fanchieh Yee, Ching Zhou, Pong-Fei Lu, Brian W. Curran, Leland Chang, Kailash Gopalakrishnan
2018	J	`jnl`	Bridging the Accuracy Gap for 2-bit Quantized Neural Networks (QNN). CoRR Jungwook Choi, Pierce I-Jen Chuang, Zhuo Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan
2018	A*	`conf`	Compensated-DNN: energy efficient low-precision deep neural networks by compensating quantization errors. DAC Shubham Jain, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Pierce Chuang, Leland Chang
2018	A*	`conf`	Dyhard-DNN: even more DNN acceleration with dynamic hardware reconfiguration. DAC Mateja Putic, Swagath Venkataramani, Schuyler Eldridge, Alper Buyuktosunoglu, Pradip Bose, Mircea Stan
2018	J	`jnl`	Energy-Efficient Neural Computing with Approximate Multipliers. ACM J. Emerg. Technol. Comput. Syst. Syed Shakib Sarwar, Swagath Venkataramani, Aayush Ankit, Anand Raghunathan, Kaushik Roy
2018	A	`conf`	Exploiting approximate computing for deep learning acceleration. DATE Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Viji Srinivasan, Swagath Venkataramani
2018	J	`jnl`	PACT: Parameterized Clipping Activation for Quantized Neural Networks. CoRR Jungwook Choi, Zhuo Wang, Swagath Venkataramani, Pierce I-Jen Chuang, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan
2018	A	`conf`	Taming the beast: Programming Peta-FLOP class Deep Learning Systems. ISLPED Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang
2018	J	`jnl`	Workload-aware Automatic Parallelization for Multi-GPU DNN Training. CoRR Sungho Shin, Youngmin Jo, Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wonyong Sung
2017	A	`conf`	A Programmable Event-driven Architecture for Evaluating Spiking Neural Networks. ISLPED Arnab Roy, Swagath Venkataramani, Neel Gala, Sanchari Sen, Kamakoti Veezhinathan, Anand Raghunathan
2017	A*	`conf`	Accelerator Design for Deep Learning Training: Extended Abstract: Invited. DAC Ankur Agrawal, Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Jinwook Oh, Sunil Shukla, Viji Srinivasan, Swagath Venkataramani, Wei Zhang
2017	J	`jnl`	Approximate Error Detection With Stochastic Checkers. IEEE Trans. Very Large Scale Integr. Syst. Neel Gala, Swagath Venkataramani, Anand Raghunathan, V. Kamakoti
2017	A	`conf`	Approximate computing for spiking neural networks. DATE Sanchari Sen, Swagath Venkataramani, Anand Raghunathan
2017	J	`jnl`	DyVEDeep: Dynamic Variable Effort Deep Neural Networks. CoRR Sanjay Ganapathy, Swagath Venkataramani, Balaraman Ravindran, Anand Raghunathan
2017	J	`jnl`	Energy-Efficient Object Detection Using Semantic Decomposition. IEEE Trans. Very Large Scale Integr. Syst. Priyadarshini Panda, Swagath Venkataramani, Abhronil Sengupta, Anand Raghunathan, Kaushik Roy
2017	J	`jnl`	Energy-Efficient Reduce-and-Rank Using Input-Adaptive Approximations. IEEE Trans. Very Large Scale Integr. Syst. Arnab Raha, Swagath Venkataramani, Vijay Raghunathan, Anand Raghunathan
2017	B	`conf`	POSTER: Design Space Exploration for Performance Optimization of Deep Neural Networks on Shared Memory Accelerators. PACT Swagath Venkataramani, Jungwook Choi, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan, Leland Chang
2017	A	`conf`	STAxCache: An approximate, energy efficient STT-MRAM cache. DATE Ashish Ranjan, Swagath Venkataramani, Zoha Pajouhi, Rangharajan Venkatesan, Kaushik Roy, Anand Raghunathan
2017	A*	`conf`	ScaleDeep: A Scalable Compute Architecture for Learning and Evaluating Deep Networks. ISCA Swagath Venkataramani, Ashish Ranjan, Subarno Banerjee, Dipankar Das, Sasikanth Avancha, Ashok Jagannathan, Ajaya Durg, Dheemanth Nagaraj, Bharat Kaul, Pradeep Dubey, Anand Raghunathan
2017	J	`jnl`	SparCE: Sparsity aware General Purpose Core Extensions to Accelerate Deep Neural Networks. CoRR Sanchari Sen, Shubham Jain, Swagath Venkataramani, Anand Raghunathan
2017	C	`conf`	Very Low Voltage (VLV) Design. ICCD Ramon Bertran, Pradip Bose, David M. Brooks, Jeff Burns, Alper Buyuktosunoglu, Nandhini Chandramoorthy, Eric Cheng, Martin Cochet, Schuyler Eldridge, Daniel J. Friedman, Hans M. Jacobson, Rajiv V. Joshi, Subhasish Mitra, Robert K. Montoye, Arun Paidimarri, Pritish Parida, Kevin Skadron, Mircea Stan, Karthik Swaminathan, Augusto Vega, Swagath Venkataramani, Christos Vezyrtzis, Gu-Yeon Wei, John-David Wellman, Matthew M. Ziegler
2016	Misc	`conf`	Approximate Computing. VLSID Swagath Venkataramani, Kaushik Roy, Anand Raghunathan
2016	—	`—`	Approximate computing: An integrated cross-layer framework Swagath Venkataramani
2016	A	`conf`	Approximation through logic isolation for the design of quality configurable circuits. DATE Shubham Jain, Swagath Venkataramani, Anand Raghunathan
2016	A*	`conf`	Designing approximate circuits using clock overgating. DAC Younghoon Kim, Swagath Venkataramani, Kaushik Roy, Anand Raghunathan
2016	J	`jnl`	EMBIRA: An Accelerator for Model-Based Iterative Reconstruction. IEEE Trans. Very Large Scale Integr. Syst. Junshi Liu, Swagath Venkataramani, Singanallur V. Venkatakrishnan, Yun Pan, Charles A. Bouman, Anand Raghunathan
2016	—	`conf`	Efficient embedded learning for IoT devices. ASP-DAC Swagath Venkataramani, Kaushik Roy, Anand Raghunathan
2016	A*	`conf`	Invited - Cross-layer approximations for neuromorphic computing: from devices to circuits and systems. DAC Priyadarshini Panda, Abhronil Sengupta, Syed Shakib Sarwar, Gopalakrishnan Srinivasan, Swagath Venkataramani, Anand Raghunathan, Kaushik Roy
2016	J	`jnl`	Multiplier-less Artificial Neurons Exploiting Error Resiliency for Energy-Efficient Neural Computing. CoRR Syed Shakib Sarwar, Swagath Venkataramani, Anand Raghunathan, Kaushik Roy
2016	A	`conf`	Multiplier-less Artificial Neurons exploiting error resiliency for energy-efficient neural computing. DATE Syed Shakib Sarwar, Swagath Venkataramani, Anand Raghunathan, Kaushik Roy
2016	A	`conf`	STOCK: Stochastic Checkers for Low-overhead Approximate Error Detection. ISLPED Neel Gala, Swagath Venkataramani, Anand Raghunathan, V. Kamakoti
2015	A*	`conf`	Approximate computing and the quest for computing efficiency. DAC Swagath Venkataramani, Srimat T. Chakradhar, Kaushik Roy, Anand Raghunathan
2015	A*	`conf`	Approximate storage for energy efficient spintronic memories. DAC Ashish Ranjan, Swagath Venkataramani, Xuanyao Fong, Kaushik Roy, Anand Raghunathan
2015	A	`conf`	Computing approximately, and efficiently. DATE Swagath Venkataramani, Srimat T. Chakradhar, Kaushik Roy, Anand Raghunathan
2015	—	`ch.`	Exploiting On-Device Image Classification for Energy Efficiency in Ambient-Aware Systems. Mobile Cloud Visual Media Computing Mohammed Shoaib, Swagath Venkataramani, Xian-Sheng Hua, Jie Liu, Jin Li
2015	J	`jnl`	Exploring Spin-Transfer-Torque Devices for Logic Applications. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Zoha Pajouhi, Swagath Venkataramani, Karthik Yogendra, Anand Raghunathan, Kaushik Roy
2015	J	`jnl`	Object Detection using Semantic Decomposition for Energy-Efficient Neural Computing. CoRR Priyadarshini Panda, Abhronil Sengupta, Swagath Venkataramani, Anand Raghunathan, Kaushik Roy
2015	A	`conf`	Quality configurable reduce-and-rank for energy efficient approximate computing. DATE Arnab Raha, Swagath Venkataramani, Vijay Raghunathan, Anand Raghunathan
2015	A	`conf`	SAPPHIRE: an always-on context-aware computer vision system for portable devices. DATE Swagath Venkataramani, Victor Bahl, Xian-Sheng Hua, Jie Liu, Jin Li, Matthai Philipose, Bodhi Priyantha, Mohammed Shoaib
2015	A*	`conf`	Scalable-effort classifiers for energy-efficient machine learning. DAC Swagath Venkataramani, Anand Raghunathan, Jie Liu, Mohammed Shoaib
2015	A	`conf`	Spintastic: <u>spin</u>-based s<u>t</u>och<u>astic</u> logic for energy-efficient computing. DATE Rangharajan Venkatesan, Swagath Venkataramani, Xuanyao Fong, Kaushik Roy, Anand Raghunathan
2014	A	`conf`	ASLAN: Synthesis of approximate sequential circuits. DATE Ashish Ranjan, Arnab Raha, Swagath Venkataramani, Kaushik Roy, Anand Raghunathan
2014	—	`conf`	Approximate computing for efficient information processing. ESTIMedia Swagath Venkataramani, Srimat T. Chakradhar, Kaushik Roy, Anand Raghunathan
2014	A	`conf`	AxNN: energy-efficient neuromorphic systems using approximate computing. ISLPED Swagath Venkataramani, Ashish Ranjan, Kaushik Roy, Anand Raghunathan
2014	A*	`conf`	STAG: Spintronic-Tape Architecture for GPGPU cache hierarchies. ISCA Rangharajan Venkatesan, Shankar Ganesh Ramasubramanian, Swagath Venkataramani, Kaushik Roy, Anand Raghunathan
2014	A	`conf`	StoRM: a stochastic recognition and mining processor. ISLPED Vinay K. Chippa, Swagath Venkataramani, Kaushik Roy, Anand Raghunathan
2014	A	`conf`	Variation tolerant design of a vector processor for recognition, mining and synthesis. ISLPED Vivek Joy Kozhikkottu, Swagath Venkataramani, Sujit Dey, Anand Raghunathan
2013	Misc	`conf`	Approximate computing: An integrated hardware approach. ACSSC Vinay K. Chippa, Swagath Venkataramani, Srimat T. Chakradhar, Kaushik Roy, Anand Raghunathan
2013	A*	`conf`	Quality programmable vector processors for approximate computing. MICRO Swagath Venkataramani, Vinay K. Chippa, Srimat T. Chakradhar, Kaushik Roy, Anand Raghunathan
2013	A*	`conf`	Relax-and-retime: a methodology for energy-efficient recovery based design. DAC Shankar Ganesh Ramasubramanian, Swagath Venkataramani, Adithya Parandhaman, Anand Raghunathan
2013	A	`conf`	Substitute-and-simplify: a unified design paradigm for approximate and quality configurable circuits. DATE Swagath Venkataramani, Kaushik Roy, Anand Raghunathan
2012	A*	`conf`	SALSA: systematic logic synthesis of approximate circuits. DAC Swagath Venkataramani, Amit Sabne, Vivek Joy Kozhikkottu, Kaushik Roy, Anand Raghunathan