Vijayalakshmi Srinivasan

51 papers A* 15A 4B 6C 1Misc 2Journal 14Unranked 8

Year	Rank	Type	Title / Venue / Authors
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
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`	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
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`	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
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`	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	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	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	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`	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	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	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`	Needle: Leveraging Program Analysis to Analyze and Extract Accelerators from Whole Programs. HPCA Snehasish Kumar, Nick Sumner, Vijayalakshmi Srinivasan, Steve Margerm, Arrvindh Shriraman
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	J	`jnl`	Special Issue on Network and Parallel Computing. Int. J. Parallel Program. Vijayalakshmi Srinivasan, Yunquan Zhang
2016	—	`conf`	Approximate computing: Challenges and opportunities. ICRC Ankur Agrawal, Jungwook Choi, Kailash Gopalakrishnan, Suyog Gupta, Ravi Nair, Jinwook Oh, Daniel A. Prener, Sunil Shukla, Vijayalakshmi Srinivasan, Zehra Sura
2016	A*	`conf`	Co-designing accelerators and SoC interfaces using gem5-Aladdin. MICRO Yakun Sophia Shao, Sam Likun Xi, Vijayalakshmi Srinivasan, Gu-Yeon Wei, David M. Brooks
2016	A	`conf`	Peruse and Profit: Estimating the Accelerability of Loops. ICS Snehasish Kumar, Vijayalakshmi Srinivasan, Amirali Sharifian, Nick Sumner, Arrvindh Shriraman
2015	A	`conf`	DASX: Hardware Accelerator for Software Data Structures. ICS Snehasish Kumar, Naveen Vedula, Arrvindh Shriraman, Vijayalakshmi Srinivasan
2015	A*	`conf`	Self-contained, accurate precomputation prefetching. MICRO Islam Atta, Xin Tong, Vijayalakshmi Srinivasan, Ioana Baldini, Andreas Moshovos
2014	J	`jnl`	Comparing Implementations of Near-Data Computing with In-Memory MapReduce Workloads. IEEE Micro Seth H. Pugsley, Jeffrey Jestes, Rajeev Balasubramonian, Vijayalakshmi Srinivasan, Alper Buyuktosunoglu, Al Davis, Feifei Li
2014	B	`conf`	NDC: Analyzing the impact of 3D-stacked memory+logic devices on MapReduce workloads. ISPASS Seth H. Pugsley, Jeffrey Jestes, Huihui Zhang, Rajeev Balasubramonian, Vijayalakshmi Srinivasan, Alper Buyuktosunoglu, Al Davis, Feifei Li
2014	B	`conf`	SQRL: hardware accelerator for collecting software data structures. PACT Snehasish Kumar, Arrvindh Shriraman, Vijayalakshmi Srinivasan, Dan Lin, Jordon Phillips
2013	A*	`conf`	RECAP: A region-based cure for the common cold (cache). HPCA Jason Zebchuk, Harold W. Cain, Xin Tong, Vijayalakshmi Srinivasan, Andreas Moshovos
2012	B	`ed.`	2012 IEEE International Symposium on Performance Analysis of Systems & Software, New Brunswick, NJ, USA, April 1-3, 2012 ISPASS Rajeev Balasubramonian, Vijayalakshmi Srinivasan
2012	—	`conf`	Programming with relaxed synchronization. RACES@SPLASH Lakshminarayanan Renganarayana, Vijayalakshmi Srinivasan, Ravi Nair, Daniel A. Prener
2012	B	`conf`	ReCaP: a region-based cure for the common cold cache. PACT Jason Zebchuk, Harold W. Cain, Vijayalakshmi Srinivasan, Andreas Moshovos
2011	J	`jnl`	Big Chips. IEEE Micro Andrew B. Kahng, Vijayalakshmi Srinivasan
2011	B	`conf`	SPATL: Honey, I Shrunk the Coherence Directory. PACT Hongzhou Zhao, Arrvindh Shriraman, Sandhya Dwarkadas, Vijayalakshmi Srinivasan
2010	A*	`conf`	SAFER: Stuck-At-Fault Error Recovery for Memories. MICRO Nak Hee Seong, Dong Hyuk Woo, Vijayalakshmi Srinivasan, Jude A. Rivers, Hsien-Hsin S. Lee
2009	A*	`conf`	A tagless coherence directory. MICRO Jason Zebchuk, Vijayalakshmi Srinivasan, Moinuddin K. Qureshi, Andreas Moshovos
2009	A*	`conf`	Enhancing lifetime and security of PCM-based main memory with start-gap wear leveling. MICRO Moinuddin K. Qureshi, John P. Karidis, Michele Franceschini, Vijayalakshmi Srinivasan, Luis A. Lastras, Bülent Abali
2009	A*	`conf`	Scalable high performance main memory system using phase-change memory technology. ISCA Moinuddin K. Qureshi, Vijayalakshmi Srinivasan, Jude A. Rivers
2008	J	`jnl`	Analyzing the Cost of a Cache Miss Using Pipeline Spectroscopy. J. Instr. Level Parallelism Thomas R. Puzak, Allan Hartstein, Philip G. Emma, Vijayalakshmi Srinivasan, Arthur Nadas
2008	J	`jnl`	On the Nature of Cache Miss Behavior: Is It √2? J. Instr. Level Parallelism Allan Hartstein, Vijayalakshmi Srinivasan, Thomas R. Puzak, Philip G. Emma
2001	—	`—`	Hardware solutions to reduce effective memory access time. Vijayalakshmi Srinivasan
1999	J	`jnl`	Active Management of Data Caches by Exploiting Reuse Information. IEEE Trans. Computers Edward S. Tam, Jude A. Rivers, Vijayalakshmi Srinivasan, Gary S. Tyson, Edward S. Davidson
1998	C	`conf`	Evaluating the performance of active cache management schemes. ICCD Edward S. Tam, Jude A. Rivers, Vijayalakshmi Srinivasan, Gary S. Tyson, Edward S. Davidson