David S. Kung

Publication Activity (10 Years)

Years Active: 1992-2021
Publications (10 Years): 21

Top Topics

Automatic Speech Recognition

Acoustic Models

Top Venues

Conf. Computing Frontiers

IBM J. Res. Dev.

Publications

Rameswar Panda, Michele Merler, Mayoore S. Jaiswal, Hui Wu, Kandan Ramakrishnan, Ulrich Finkler, Chun-Fu (Richard) Chen, Minsik Cho, Rogério Feris, David S. Kung, Bishwaranjan Bhattacharjee
NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search. AAAI (2021)
Xiaodong Cui, Wei Zhang, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, David S. Kung
Asynchronous Decentralized Distributed Training of Acoustic Models. IEEE ACM Trans. Audio Speech Lang. Process. 29 (2021)
Ruchir Puri, David S. Kung, Geert Janssen, Wei Zhang, Giacomo Domeniconi, Vladimir Zolotov, Julian Dolby, Jie Chen, Mihir R. Choudhury, Lindsey Decker, Veronika Thost, Luca Buratti, Saurabh Pujar, Shyam Ramji, Ulrich Finkler, Susan Malaika, Frederick Reiss
CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks. NeurIPS Datasets and Benchmarks (2021)
Xiaodong Cui, Wei Zhang, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, David S. Kung
Asynchronous Decentralized Distributed Training of Acoustic Models. CoRR (2021)
Ruchir Puri, David S. Kung, Geert Janssen, Wei Zhang, Giacomo Domeniconi, Vladimir Zolotov, Julian Dolby, Jie Chen, Mihir R. Choudhury, Lindsey Decker, Veronika Thost, Luca Buratti, Saurabh Pujar, Ulrich Finkler
Project CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks. CoRR (2021)
Wei Zhang, Xiaodong Cui, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, Youssef Mroueh, Alper Buyuktosunoglu, Payel Das, David S. Kung, Michael Picheny
Improving Efficiency in Large-Scale Decentralized Distributed Training. ICASSP (2020)
Rui Zhang, Conrad M. Albrecht, Wei Zhang, Xiaodong Cui, Ulrich Finkler, David S. Kung, Siyuan Lu
Map Generation from Large Scale Incomplete and Inaccurate Data Labels. KDD (2020)
Rameswar Panda, Michele Merler, Mayoore Jaiswal, Hui Wu, Kandan Ramakrishnan, Ulrich Finkler, Chun-Fu Chen, Minsik Cho, David S. Kung, Rogério Feris, Bishwaranjan Bhattacharjee
NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search. CoRR (2020)
Ulrich Finkler, Michele Merler, Rameswar Panda, Mayoore S. Jaiswal, Hui Wu, Kandan Ramakrishnan, Chun-Fu Chen, Minsik Cho, David S. Kung, Rogério Feris, Bishwaranjan Bhattacharjee
Large Scale Neural Architecture Search with Polyharmonic Splines. CoRR (2020)
Rui Zhang, Conrad M. Albrecht, Wei Zhang, Xiaodong Cui, Ulrich Finkler, David S. Kung, Siyuan Lu
Map Generation from Large Scale Incomplete and Inaccurate Data Labels. CoRR (2020)
Xiaodong Cui, Wei Zhang, Ulrich Finkler, George Saon, Michael Picheny, David S. Kung
Distributed Training of Deep Neural Network Acoustic Models for Automatic Speech Recognition. CoRR (2020)
Xiaodong Cui, Wei Zhang, Ulrich Finkler, George Saon, Michael Picheny, David S. Kung
Distributed Training of Deep Neural Network Acoustic Models for Automatic Speech Recognition: A comparison of current training strategies. IEEE Signal Process. Mag. 37 (3) (2020)
Wei Zhang, Xiaodong Cui, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, Youssef Mroueh, Alper Buyuktosunoglu, Payel Das, David S. Kung, Michael Picheny
Improving Efficiency in Large-Scale Decentralized Distributed Training. CoRR (2020)
Wei Zhang, Xiaodong Cui, Ulrich Finkler, George Saon, Abdullah Kayi, Alper Buyuktosunoglu, Brian Kingsbury, David S. Kung, Michael Picheny
A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition. CoRR (2019)
Wei Zhang, Xiaodong Cui, Ulrich Finkler, George Saon, Abdullah Kayi, Alper Buyuktosunoglu, Brian Kingsbury, David S. Kung, Michael Picheny
A Highly Efficient Distributed Deep Learning System for Automatic Speech Recognition. INTERSPEECH (2019)
Wei Zhang, Xiaodong Cui, Ulrich Finkler, Brian Kingsbury, George Saon, David S. Kung, Michael Picheny
Distributed Deep Learning Strategies for Automatic Speech Recognition. ICASSP (2019)
Wei Zhang, Xiaodong Cui, Ulrich Finkler, Brian Kingsbury, George Saon, David S. Kung, Michael Picheny
Distributed Deep Learning Strategies For Automatic Speech Recognition. CoRR (2019)
Minsik Cho, Ulrich Finkler, Mauricio J. Serrano, David S. Kung, Hillery C. Hunter
BlueConnect: Decomposing all-reduce for deep learning on heterogeneous network hierarchy. IBM J. Res. Dev. 63 (6) (2019)
Minsik Cho, Ulrich Finkler, David S. Kung, Hillery C. Hunter
BlueConnect: Decomposing All-Reduce for Deep Learning on Heterogeneous Network Hierarchy. MLSys (2019)
Minsik Cho, Ulrich Finkler, Sameer Kumar, David S. Kung, Vaibhav Saxena, Dheeraj Sreedhar
PowerAI DDL. CoRR (2017)
Ulrich Finkler, Hubertus Franke, David S. Kung
DYCE: A Resilient Shared Memory Paradigm for Heterogenous Distributed Systems without Memory Coherence. Conf. Computing Frontiers (2017)
Ruchir Puri, David S. Kung
The Dawn of 22nm Era: Design and CAD Challenges. VLSI Design (2010)
David S. Kung
The fate of stacking. IEEE Des. Test Comput. 26 (5) (2009)
David S. Kung, Yuan Xie
Guest Editors' Introduction: Opportunities and Challenges of 3D Integration. IEEE Des. Test Comput. 26 (5) (2009)
David S. Kung, Ruchir Puri
CAD challenges for 3D ICs. ASP-DAC (2009)
Haoxing Ren, David Zhigang Pan, David S. Kung
Sensitivity guided net weighting for placement-driven synthesis. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 24 (5) (2005)
Ruchir Puri, David S. Kung, Leon Stok
Minimizing power with flexible voltage islands. ISCAS (1) (2005)
Renato Fernandes Hentschke, Jagannathan Narasimhan, David S. Kung
Improving run times by pruned application of synthesis transforms. SBCCI (2005)
Louise Trevillyan, David S. Kung, Ruchir Puri, Lakshmi N. Reddy, Michael A. Kazda
An Integrated Environment for Technology Closure of Deep-Submicron IC Designs. IEEE Des. Test Comput. 21 (1) (2004)
David S. Kung
Timing closure for low-FO4 microprocessor design. DAC (2004)
Haoxing Ren, David Zhigang Pan, David S. Kung
Sensitivity guided net weighting for placement driven synthesis. ISPD (2004)
Ruchir Puri, Leon Stok, John M. Cohn, David S. Kung, David Z. Pan, Dennis Sylvester, Ashish Srivastava, Sarvesh H. Kulkarni
Pushing ASIC performance in a power envelope. DAC (2003)
Ruchir Puri, David S. Kung, Anthony D. Drumm
Fast and accurate wire delay estimation for physical synthesis of large ASICs. ACM Great Lakes Symposium on VLSI (2002)
Frederik Beeftink, Prabhakar Kudva, David S. Kung, Ruchir Puri, Leon Stok
Combinatorial cell design for CMOS libraries. Integr. 29 (1) (2000)
David S. Kung, Ruchir Puri
Optimal P/N width ratio selection for standard cell libraries. ICCAD (1999)
David S. Kung
A Fast Fanout Optimization Algorithm for Near-Continuous Buffer Libraries. DAC (1998)
Frederik Beeftink, Prabhakar Kudva, David S. Kung, Leon Stok
Gate-size selection for standard cell libraries. ICCAD (1998)
Leon Stok, David S. Kung, Daniel Brand, Anthony D. Drumm, Andrew J. Sullivan, Lakshmi N. Reddy, Nathaniel Hieter, David J. Geiger, Han Hsun Chao, Peter J. Osler
BooleDozer: Logic synthesis for ASICs. IBM J. Res. Dev. 40 (4) (1996)
David S. Kung, Robert F. Damiano, Theresa A. Nix, David J. Geiger
BDDMAP: A Technology Mapper Based on a New Covering Algorithm. DAC (1992)
David S. Kung
Hazard-non-increasing gate-level optimization algorithms. ICCAD (1992)