Kailash Gopalakrishnan

49 papers A* 10A 5B 2C 1Misc 2Journal 19Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AI+HW 2035: Shaping the Next Decade. CoRR Deming Chen, Jason Cong, Azalia Mirhoseini, Christos Kozyrakis, Subhasish Mitra, Jinjun Xiong, Cliff Young, Anima Anandkumar, Michael L. Littman, Aron Kirschen, Sophia Shao, Serge Leef, Naresh R. Shanbhag, Dejan S. Milojicic, Michael Schulte, Gert Cauwenberghs, Jerry M. Chow, Tri Dao, Kailash Gopalakrishnan, Richard Ho, Hoshik Kim, Kunle Olukotun, David Z. Pan, Mark Ren, Dan Roth, Aarti Singh, Yizhou Sun, Yusu Wang, Yann LeCun, Ruchir Puri
2023	—	`conf`	A Switched-Capacitor Integer Compute Unit with Decoupled Storage and Arithmetic for Cloud AI Inference in 5nm CMOS. VLSI Technology and Circuits Ankur Agrawal, Monodeep Kar, Kyu-Hyoun Kim, Sergey V. Rylov, Jinwook Jung, Seiji Munetoh, Kohji Hosokawa, Xin Zhang, Bahman Hekmatshoartabari, Fabio Carta, Martin Cochet, Robert Casatuta, Mingu Kang, Sunil Shukla, Kailash Gopalakrishnan, Leland Chang
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	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	J	`jnl`	All at Once Network Quantization via Collaborative Knowledge Transfer. CoRR Ximeng Sun, Rameswar Panda, Chun-Fu Chen, Naigang Wang, Bowen Pan, Kailash Gopalakrishnan, Aude Oliva, Rogério Feris, Kate Saenko
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
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`	FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training. NeurIPS Yonggan Fu, Haoran You, Yang Zhao, Yue Wang, Chaojian Li, Kailash Gopalakrishnan, Zhangyang Wang, Yingyan Lin
2020	J	`jnl`	FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training. CoRR Yonggan Fu, Haoran You, Yang Zhao, Yue Wang, Chaojian Li, Kailash Gopalakrishnan, Zhangyang Wang, Yingyan Lin
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`	Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. ICLR (Poster) Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, Kailash Gopalakrishnan
2019	J	`jnl`	Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. CoRR Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, 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	C	`conf`	DLFloat: A 16-b Floating Point Format Designed for Deep Learning Training and Inference. ARITH Ankur Agrawal, Bruce M. Fleischer, Silvia M. Mueller, Xiao Sun, Naigang Wang, Jungwook Choi, Kailash Gopalakrishnan
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
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	A*	`conf`	AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training. AAAI Chia-Yu Chen, Jungwook Choi, Daniel Brand, Ankur Agrawal, Wei Zhang, 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`	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	A*	`conf`	Training Deep Neural Networks with 8-bit Floating Point Numbers. NeurIPS Naigang Wang, Jungwook Choi, Daniel Brand, Chia-Yu Chen, Kailash Gopalakrishnan
2018	J	`jnl`	Training Deep Neural Networks with 8-bit Floating Point Numbers. CoRR Naigang Wang, Jungwook Choi, Daniel Brand, Chia-Yu Chen, Kailash Gopalakrishnan
2018	Misc	`conf`	True Gradient-Based Training of Deep Binary Activated Neural Networks Via Continuous Binarization. ICASSP Charbel Sakr, Jungwook Choi, Zhuo Wang, Kailash Gopalakrishnan, Naresh R. Shanbhag
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`	AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training. CoRR Chia-Yu Chen, Jungwook Choi, Daniel Brand, Ankur Agrawal, Wei Zhang, Kailash Gopalakrishnan
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
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	—	`conf`	Energy-Efficient Simultaneous Localization and Mapping via Compounded Approximate Computing. SiPS Jinwook Oh, Jungwook Choi, Guilherme C. Januario, Kailash Gopalakrishnan
2015	A*	`conf`	Deep Learning with Limited Numerical Precision. ICML Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, Pritish Narayanan
2015	J	`jnl`	Deep Learning with Limited Numerical Precision. CoRR Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, Pritish Narayanan
2014	J	`jnl`	Learning Machines Implemented on Non-Deterministic Hardware. CoRR Suyog Gupta, Vikas Sindhwani, Kailash Gopalakrishnan
2013	J	`jnl`	Nanoscale electronic synapses using phase change devices. ACM J. Emerg. Technol. Comput. Syst. Bryan L. Jackson, Bipin Rajendran, Gregory S. Corrado, Matthew J. Breitwisch, Geoffrey W. Burr, Roger Cheek, Kailash Gopalakrishnan, Simone Raoux, Charles T. Rettner, Alvaro Padilla, Alejandro G. Schrott, Rohit S. Shenoy, Bülent N. Kurdi, Chung Hon Lam, Dharmendra S. Modha
2008	J	`jnl`	Overview of candidate device technologies for storage-class memory. IBM J. Res. Dev. Geoffrey W. Burr, Bülent N. Kurdi, J. Campbell Scott, Chung Hon Lam, Kailash Gopalakrishnan, Rohit S. Shenoy