Swagath Venkataramani
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
49
Venues
15
Active years
2012–2026
Best venue rank
A*
Where they publish
Papers
49 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | CGO | Eliminating Redundancy: Ultra-compact Code Generation for Programmable Dataflow Accelerators. | 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 | CGO | Enabling Spill-Free Compilation via Affine-Based Live Range Reduction Optimization. | Prasanth Chatarasi, Alex Gatea, Wei Wang, Chris Bowler, Shubham Jain, Masoud Ataei Jaliseh, Nicole Khoun, Alberto Mannari, Bardia Mahjour, Viji Srinivasan, Swagath Venkataramani |
| 2022 | ICCAD | Approximate Computing and the Efficient Machine Learning Expedition. | Jrg Henkel, Hai Li, Anand Raghunathan, Mehdi B. Tahoori, Swagath Venkataramani, Xiaoxuan Yang, Georgios Zervakis |
| 2022 | Interspeech | Accelerating Inference and Language Model Fusion of Recurrent Neural Network Transducers via End-to-End 4-bit Quantization. | Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Kailash Gopalakrishnan |
| 2021 | DATE | Value Similarity Extensions for Approximate Computing in General-Purpose Processors. | Younghoon Kim, Swagath Venkataramani, Sanchari Sen, Anand Raghunathan |
| 2021 | Interspeech | 4-Bit Quantization of LSTM-Based Speech Recognition Models. | Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Xiao Sun, Naigang Wang, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Wei Zhang, Zoltn Tske, Kailash Gopalakrishnan |
| 2021 | ISCA | 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 |
| 2021 | ISLPED | Efficacy of Pruning in Ultra-Low Precision DNNs. | Sanchari Sen, Swagath Venkataramani, Anand Raghunathan |
| 2021 | ISPASS | Efficient Management of Scratch-Pad Memories in Deep Learning Accelerators. | Subhankar Pal, Swagath Venkataramani, Viji Srinivasan, Kailash Gopalakrishnan |
| 2019 | DAC | BiScaled-DNN: Quantizing Long-tailed Datastructures with Two Scale Factors for Deep Neural Networks. | Shubham Jain, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang |
| 2019 | DATE | Data Subsetting: A Data-Centric Approach to Approximate Computing. | Younghoon Kim, Swagath Venkataramani, Nitin Chandrachoodan, Anand Raghunathan |
| 2019 | HiPC | Memory and Interconnect Optimizations for Peta-Scale Deep Learning Systems. | Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Philip Heidelberger, Leland Chang, Kailash Gopalakrishnan |
| 2019 | ICASSP | Workload-aware Automatic Parallelization for Multi-GPU DNN Training. | Sungho Shin, Youngmin Jo, Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wonyong Sung |
| 2019 | ISLPED | Dynamic Spike Bundling for Energy-Efficient Spiking Neural Networks. | Sarada Krithivasan, Sanchari Sen, Swagath Venkataramani, Anand Raghunathan |
| 2018 | DAC | Compensated-DNN: energy efficient low-precision deep neural networks by compensating quantization errors. | Shubham Jain, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Pierce Chuang, Leland Chang |
| 2018 | DAC | Dyhard-DNN: even more DNN acceleration with dynamic hardware reconfiguration. | Mateja Putic, Swagath Venkataramani, Schuyler Eldridge, Alper Buyuktosunoglu, Pradip Bose, Mircea Stan |
| 2018 | DATE | Exploiting approximate computing for deep learning acceleration. | Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Viji Srinivasan, Swagath Venkataramani |
| 2018 | ISLPED | Across the Stack Opportunities for Deep Learning Acceleration. | 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 | ISLPED | Taming the beast: Programming Peta-FLOP class Deep Learning Systems. | Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang |
| 2017 | DAC | Accelerator Design for Deep Learning Training: Extended Abstract: Invited. | Ankur Agrawal, Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Jinwook Oh, Sunil Shukla, Viji Srinivasan, Swagath Venkataramani, Wei Zhang |
| 2017 | DATE | STAxCache: An approximate, energy efficient STT-MRAM cache. | Ashish Ranjan, Swagath Venkataramani, Zoha Pajouhi, Rangharajan Venkatesan, Kaushik Roy, Anand Raghunathan |
| 2017 | DATE | Approximate computing for spiking neural networks. | Sanchari Sen, Swagath Venkataramani, Anand Raghunathan |
| 2017 | ICCD | Very Low Voltage (VLV) Design. | 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 |
| 2017 | ISCA | ScaleDeep: A Scalable Compute Architecture for Learning and Evaluating Deep Networks. | Swagath Venkataramani, Ashish Ranjan, Subarno Banerjee, Dipankar Das, Sasikanth Avancha, Ashok Jagannathan, Ajaya Durg, Dheemanth Nagaraj, Bharat Kaul, Pradeep Dubey, Anand Raghunathan |
| 2017 | ISLPED | A Programmable Event-driven Architecture for Evaluating Spiking Neural Networks. | Arnab Roy, Swagath Venkataramani, Neel Gala, Sanchari Sen, Kamakoti Veezhinathan, Anand Raghunathan |
| 2016 | ASPDAC | Efficient embedded learning for IoT devices. | Swagath Venkataramani, Kaushik Roy, Anand Raghunathan |
| 2016 | DAC | Designing approximate circuits using clock overgating. | Younghoon Kim, Swagath Venkataramani, Kaushik Roy, Anand Raghunathan |
| 2016 | DAC | Invited - Cross-layer approximations for neuromorphic computing: from devices to circuits and systems. | Priyadarshini Panda, Abhronil Sengupta, Syed Shakib Sarwar, Gopalakrishnan Srinivasan, Swagath Venkataramani, Anand Raghunathan, Kaushik Roy |
| 2016 | DATE | Approximation through logic isolation for the design of quality configurable circuits. | Shubham Jain, Swagath Venkataramani, Anand Raghunathan |
| 2016 | DATE | Multiplier-less Artificial Neurons exploiting error resiliency for energy-efficient neural computing. | Syed Shakib Sarwar, Swagath Venkataramani, Anand Raghunathan, Kaushik Roy |
| 2016 | ISLPED | STOCK: Stochastic Checkers for Low-overhead Approximate Error Detection. | Neel Gala, Swagath Venkataramani, Anand Raghunathan, V. Kamakoti |
| 2016 | VLSID | Approximate Computing. | Swagath Venkataramani, Kaushik Roy, Anand Raghunathan |
| 2015 | DAC | Approximate storage for energy efficient spintronic memories. | Ashish Ranjan, Swagath Venkataramani, Xuanyao Fong, Kaushik Roy, Anand Raghunathan |
| 2015 | DAC | Approximate computing and the quest for computing efficiency. | Swagath Venkataramani, Srimat T. Chakradhar, Kaushik Roy, Anand Raghunathan |
| 2015 | DAC | Scalable-effort classifiers for energy-efficient machine learning. | Swagath Venkataramani, Anand Raghunathan, Jie Liu, Mohammed Shoaib |
| 2015 | DATE | Quality configurable reduce-and-rank for energy efficient approximate computing. | Arnab Raha, Swagath Venkataramani, Vijay Raghunathan, Anand Raghunathan |
| 2015 | DATE | SAPPHIRE: an always-on context-aware computer vision system for portable devices. | Swagath Venkataramani, Victor Bahl, Xian-Sheng Hua, Jie Liu, Jin Li, Matthai Philipose, Bodhi Priyantha, Mohammed Shoaib |
| 2015 | DATE | Computing approximately, and efficiently. | Swagath Venkataramani, Srimat T. Chakradhar, Kaushik Roy, Anand Raghunathan |
| 2015 | DATE | Spintastic: <u>spin</u>-based s<u>t</u>och<u>astic</u> logic for energy-efficient computing. | Rangharajan Venkatesan, Swagath Venkataramani, Xuanyao Fong, Kaushik Roy, Anand Raghunathan |
| 2014 | DATE | ASLAN: Synthesis of approximate sequential circuits. | Ashish Ranjan, Arnab Raha, Swagath Venkataramani, Kaushik Roy, Anand Raghunathan |
| 2014 | ISCA | STAG: Spintronic-Tape Architecture for GPGPU cache hierarchies. | Rangharajan Venkatesan, Shankar Ganesh Ramasubramanian, Swagath Venkataramani, Kaushik Roy, Anand Raghunathan |
| 2014 | ISLPED | StoRM: a stochastic recognition and mining processor. | Vinay K. Chippa, Swagath Venkataramani, Kaushik Roy, Anand Raghunathan |
| 2014 | ISLPED | Variation tolerant design of a vector processor for recognition, mining and synthesis. | Vivek Joy Kozhikkottu, Swagath Venkataramani, Sujit Dey, Anand Raghunathan |
| 2014 | ISLPED | AxNN: energy-efficient neuromorphic systems using approximate computing. | Swagath Venkataramani, Ashish Ranjan, Kaushik Roy, Anand Raghunathan |
| 2013 | ACSSC | Approximate computing: An integrated hardware approach. | Vinay K. Chippa, Swagath Venkataramani, Srimat T. Chakradhar, Kaushik Roy, Anand Raghunathan |
| 2013 | DAC | Relax-and-retime: a methodology for energy-efficient recovery based design. | Shankar Ganesh Ramasubramanian, Swagath Venkataramani, Adithya Parandhaman, Anand Raghunathan |
| 2013 | DATE | Substitute-and-simplify: a unified design paradigm for approximate and quality configurable circuits. | Swagath Venkataramani, Kaushik Roy, Anand Raghunathan |
| 2013 | MICRO | Quality programmable vector processors for approximate computing. | Swagath Venkataramani, Vinay K. Chippa, Srimat T. Chakradhar, Kaushik Roy, Anand Raghunathan |
| 2012 | DAC | SALSA: systematic logic synthesis of approximate circuits. | Swagath Venkataramani, Amit Sabne, Vivek Joy Kozhikkottu, Kaushik Roy, Anand Raghunathan |