Vijayalakshmi Srinivasan

Publication Activity (10 Years)

Years Active: 1998-2022
Publications (10 Years): 30

Top Topics

Top Venues

Publications

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)
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
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 57 (1) (2022)
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
A 7nm 4-Core AI Chip with 25.6TFLOPS Hybrid FP8 Training, 102.4TOPS INT4 Inference and Workload-Aware Throttling. ISSCC (2021)
Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training. CoRR (2021)
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)
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
Efficient AI System Design With Cross-Layer Approximate Computing. Proc. IEEE 108 (12) (2020)
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
A 3.0 TFLOPS 0.62V Scalable Processor Core for High Compute Utilization AI Training and Inference. VLSI Circuits (2020)
Xiao Sun, Naigang Wang, Chia-Yu Chen, Jiamin Ni, Ankur Agrawal, Xiaodong Cui, Swagath Venkataramani, Kaoutar El Maghraoui, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan
Ultra-Low Precision 4-bit Training of Deep Neural Networks. NeurIPS (2020)
Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training. NeurIPS (2020)
Shubham Jain, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang
BiScaled-DNN: Quantizing Long-tailed Datastructures with Two Scale Factors for Deep Neural Networks. DAC (2019)
Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan, Zhuo Wang, Pierce Chuang
Accurate and Efficient 2-bit Quantized Neural Networks. MLSys (2019)
Eri Ogawa, Kazuaki Ishizaki, Hiroshi Inoue, Swagath Venkataramani, Jungwook Choi, Wei Wang, Vijayalakshmi Srinivasan, Moriyoshi Ohara, Kailash Gopalakrishnan
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 (2019)
Sungho Shin, Youngmin Jo, Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wonyong Sung
Workload-aware Automatic Parallelization for Multi-GPU DNN Training. ICASSP (2019)
Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Philip Heidelberger, Leland Chang, Kailash Gopalakrishnan
Memory and Interconnect Optimizations for Peta-Scale Deep Learning Systems. HiPC (2019)
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
DeepTools: Compiler and Execution Runtime Extensions for RaPiD AI Accelerator. IEEE Micro 39 (5) (2019)
Xiao Sun, Jungwook Choi, Chia-Yu Chen, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Xiaodong Cui, Wei Zhang, Kailash Gopalakrishnan
Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks. NeurIPS (2019)
Swagath Venkataramani, Jungwook Choi, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan, Leland Chang
Performance-driven Programming of Multi-TFLOP Deep Learning Accelerators. IISWC (2019)
Shubham Jain, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Pierce Chuang, Leland Chang
Compensated-DNN: energy efficient low-precision deep neural networks by compensating quantization errors. DAC (2018)
Jungwook Choi, Pierce I-Jen Chuang, Zhuo Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan
Bridging the Accuracy Gap for 2-bit Quantized Neural Networks (QNN). CoRR (2018)
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
A Scalable Multi- TeraOPS Deep Learning Processor Core for AI Trainina and Inference. VLSI Circuits (2018)
Jungwook Choi, Zhuo Wang, Swagath Venkataramani, Pierce I-Jen Chuang, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan
PACT: Parameterized Clipping Activation for Quantized Neural Networks. CoRR (2018)
Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang
Taming the beast: Programming Peta-FLOP class Deep Learning Systems. ISLPED (2018)
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
Across the Stack Opportunities for Deep Learning Acceleration. ISLPED (2018)
Sungho Shin, Youngmin Jo, Jungwook Choi, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wonyong Sung
Workload-aware Automatic Parallelization for Multi-GPU DNN Training. CoRR (2018)
Swagath Venkataramani, Jungwook Choi, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan, Leland Chang
POSTER: Design Space Exploration for Performance Optimization of Deep Neural Networks on Shared Memory Accelerators. PACT (2017)
Vijayalakshmi Srinivasan, Yunquan Zhang
Special Issue on Network and Parallel Computing. Int. J. Parallel Program. 45 (1) (2017)
Snehasish Kumar, Nick Sumner, Vijayalakshmi Srinivasan, Steve Margerm, Arrvindh Shriraman
Needle: Leveraging Program Analysis to Analyze and Extract Accelerators from Whole Programs. HPCA (2017)
Ankur Agrawal, Jungwook Choi, Kailash Gopalakrishnan, Suyog Gupta, Ravi Nair, Jinwook Oh, Daniel A. Prener, Sunil Shukla, Vijayalakshmi Srinivasan, Zehra Sura
Approximate computing: Challenges and opportunities. ICRC (2016)
Yakun Sophia Shao, Sam Likun Xi, Vijayalakshmi Srinivasan, Gu-Yeon Wei, David M. Brooks
Co-designing accelerators and SoC interfaces using gem5-Aladdin. MICRO (2016)
Snehasish Kumar, Vijayalakshmi Srinivasan, Amirali Sharifian, Nick Sumner, Arrvindh Shriraman
Peruse and Profit: Estimating the Accelerability of Loops. ICS (2016)
Snehasish Kumar, Naveen Vedula, Arrvindh Shriraman, Vijayalakshmi Srinivasan
DASX: Hardware Accelerator for Software Data Structures. ICS (2015)
Islam Atta, Xin Tong, Vijayalakshmi Srinivasan, Ioana Baldini, Andreas Moshovos
Self-contained, accurate precomputation prefetching. MICRO (2015)
Seth H. Pugsley, Jeffrey Jestes, Rajeev Balasubramonian, Vijayalakshmi Srinivasan, Alper Buyuktosunoglu, Al Davis, Feifei Li
Comparing Implementations of Near-Data Computing with In-Memory MapReduce Workloads. IEEE Micro 34 (4) (2014)
Seth H. Pugsley, Jeffrey Jestes, Huihui Zhang, Rajeev Balasubramonian, Vijayalakshmi Srinivasan, Alper Buyuktosunoglu, Al Davis, Feifei Li
NDC: Analyzing the impact of 3D-stacked memory+logic devices on MapReduce workloads. ISPASS (2014)
Snehasish Kumar, Arrvindh Shriraman, Vijayalakshmi Srinivasan, Dan Lin, Jordon Phillips
SQRL: hardware accelerator for collecting software data structures. PACT (2014)
Jason Zebchuk, Harold W. Cain, Xin Tong, Vijayalakshmi Srinivasan, Andreas Moshovos
RECAP: A region-based cure for the common cold (cache). HPCA (2013)
Jason Zebchuk, Harold W. Cain, Vijayalakshmi Srinivasan, Andreas Moshovos
ReCaP: a region-based cure for the common cold cache. PACT (2012)
Lakshminarayanan Renganarayana, Vijayalakshmi Srinivasan, Ravi Nair, Daniel A. Prener
Programming with relaxed synchronization. RACES@SPLASH (2012)
Andrew B. Kahng, Vijayalakshmi Srinivasan
Big Chips. IEEE Micro 31 (4) (2011)
Hongzhou Zhao, Arrvindh Shriraman, Sandhya Dwarkadas, Vijayalakshmi Srinivasan
SPATL: Honey, I Shrunk the Coherence Directory. PACT (2011)
Nak Hee Seong, Dong Hyuk Woo, Vijayalakshmi Srinivasan, Jude A. Rivers, Hsien-Hsin S. Lee
SAFER: Stuck-At-Fault Error Recovery for Memories. MICRO (2010)
Moinuddin K. Qureshi, Vijayalakshmi Srinivasan, Jude A. Rivers
Scalable high performance main memory system using phase-change memory technology. ISCA (2009)
Jason Zebchuk, Vijayalakshmi Srinivasan, Moinuddin K. Qureshi, Andreas Moshovos
A tagless coherence directory. MICRO (2009)
Moinuddin K. Qureshi, John P. Karidis, Michele Franceschini, Vijayalakshmi Srinivasan, Luis A. Lastras, Bülent Abali
Enhancing lifetime and security of PCM-based main memory with start-gap wear leveling. MICRO (2009)
Allan Hartstein, Vijayalakshmi Srinivasan, Thomas R. Puzak, Philip G. Emma
On the Nature of Cache Miss Behavior: Is It √2? J. Instr. Level Parallelism 10 (2008)
Thomas R. Puzak, Allan Hartstein, Philip G. Emma, Vijayalakshmi Srinivasan, Arthur Nadas
Analyzing the Cost of a Cache Miss Using Pipeline Spectroscopy. J. Instr. Level Parallelism 10 (2008)
Edward S. Tam, Jude A. Rivers, Vijayalakshmi Srinivasan, Gary S. Tyson, Edward S. Davidson
Active Management of Data Caches by Exploiting Reuse Information. IEEE Trans. Computers 48 (11) (1999)
Edward S. Tam, Jude A. Rivers, Vijayalakshmi Srinivasan, Gary S. Tyson, Edward S. Davidson
Evaluating the performance of active cache management schemes. ICCD (1998)