Rathinakumar Appuswamy

According to our database, Rathinakumar Appuswamy authored at least 32 papers between 2000 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

11.4 IBM NorthPole: An Architecture for Neural Network Inference with a 12nm Chip.

Andrew S. Cassidy, John V. Arthur, Filipp Akopyan, Alexander Andreopoulos, Rathinakumar Appuswamy, Pallab Datta, Michael V. DeBole, Steven K. Esser, Carlos Ortega Otero, Jun Sawada, Brian Taba, Arnon Amir, Deepika Bablani, Peter J. Carlson, Myron D. Flickner, Rajamohan Gandhasri, Guillaume Garreau, Megumi Ito, Jennifer L. Klamo, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Jeffrey L. McKinstry, Yutaka Y. Nakamura, Tapan K. Nayak, William P. Risk, Kai Schleupen, Ben Shaw, Jay Sivagnaname, Daniel F. Smith, Ignacio Terrizzano, Takanori Ueda, Dharmendra S. Modha

Proceedings of the IEEE International Solid-State Circuits Conference, 2024

2023

Efficient and Effective Methods for Mixed Precision Neural Network Quantization for Faster, Energy-efficient Inference.

Deepika Bablani, Jeffrey L. McKinstry, Steven K. Esser, Rathinakumar Appuswamy, Dharmendra S. Modha

CoRR, 2023

IBM NorthPole Neural Inference Machine.

Dharmendra S. Modha, Filipp Akopyan, Alexander Andreopoulos, Rathinakumar Appuswamy, John V. Arthur, Andrew S. Cassidy, Pallab Datta, Michael V. DeBole, Steven K. Esser, Carlos Ortega Otero, Jun Sawada, Brian Taba, Arnon Amir, Deepika Bablani, Peter J. Carlson, Myron D. Flickner, Rajamohan Gandhasri, Guillaume Garreau, Megumi Ito, Jennifer L. Klamo, Jeffrey A. Kusnitz, Nathaniel J. McClatchey, Jeffrey L. McKinstry, Yutaka Y. Nakamura, Tapan K. Nayak, William P. Risk, Kai Schleupen, Ben Shaw, Jay Sivagnaname, Daniel F. Smith, Ignacio Terrizzano, Takanori Ueda

Proceedings of the 35th IEEE Hot Chips Symposium, 2023

2020

Learned Step Size quantization.

Steven K. Esser, Jeffrey L. McKinstry, Deepika Bablani, Rathinakumar Appuswamy, Dharmendra S. Modha

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

TrueNorth: Accelerating From Zero to 64 Million Neurons in 10 Years.

Michael V. DeBole, Brian Taba, Arnon Amir, Filipp Akopyan, Alexander Andreopoulos, William P. Risk, Jeff Kusnitz, Carlos Ortega Otero, Tapan K. Nayak, Rathinakumar Appuswamy, Peter J. Carlson, Andrew S. Cassidy, Pallab Datta, Steven K. Esser, Guillaume Garreau, Kevin L. Holland, Scott Lekuch, Michael Mastro, Jeffrey L. McKinstry, Carmelo di Nolfo, Brent Paulovicks, Jun Sawada, Kai Schleupen, Benjamin G. Shaw, Jennifer L. Klamo, Myron D. Flickner, John V. Arthur, Dharmendra S. Modha

Computer, 2019

Discovering Low-Precision Networks Close to Full-Precision Networks for Efficient Inference.

Jeffrey L. McKinstry, Steven K. Esser, Rathinakumar Appuswamy, Deepika Bablani, John V. Arthur, Izzet B. Yildiz, Dharmendra S. Modha

Proceedings of the Fifth Workshop on Energy Efficient Machine Learning and Cognitive Computing, 2019

2018

Discovering Low-Precision Networks Close to Full-Precision Networks for Efficient Embedded Inference.

Jeffrey L. McKinstry, Steven K. Esser, Rathinakumar Appuswamy, Deepika Bablani, John V. Arthur, Izzet B. Yildiz, Dharmendra S. Modha

CoRR, 2018

2016

Convolutional networks for fast, energy-efficient neuromorphic computing.

Steven K. Esser, Paul A. Merolla, John V. Arthur, Andrew S. Cassidy, Rathinakumar Appuswamy, Alexander Andreopoulos, David J. Berg, Jeffrey L. McKinstry, Timothy Melano, Davis R. Barch, Carmelo di Nolfo, Pallab Datta, Arnon Amir, Brian Taba, Myron D. Flickner, Dharmendra S. Modha

Proc. Natl. Acad. Sci. USA, 2016

Deep neural networks are robust to weight binarization and other non-linear distortions.

Paul Merolla, Rathinakumar Appuswamy, John V. Arthur, Steven K. Esser, Dharmendra S. Modha

CoRR, 2016

Structured Convolution Matrices for Energy-efficient Deep learning.

Rathinakumar Appuswamy, Tapan K. Nayak, John V. Arthur, Steven K. Esser, Paul Merolla, Jeffrey L. McKinstry, Timothy Melano, Myron Flickner, Dharmendra S. Modha

CoRR, 2016

Truenorth ecosystem for brain-inspired computing: scalable systems, software, and applications.

Jun Sawada, Filipp Akopyan, Andrew S. Cassidy, Brian Taba, Michael V. DeBole, Pallab Datta, Rodrigo Alvarez-Icaza, Arnon Amir, John V. Arthur, Alexander Andreopoulos, Rathinakumar Appuswamy, Heinz Baier, Davis Barch, David J. Berg, Carmelo di Nolfo, Steven K. Esser, Myron Flickner, Thomas A. Horvath, Bryan L. Jackson, Jeff Kusnitz, Scott Lekuch, Michael Mastro, Timothy Melano, Paul A. Merolla, Steven E. Millman, Tapan K. Nayak, Norm Pass, Hartmut E. Penner, William P. Risk, Kai Schleupen, Benjamin G. Shaw, Hayley Wu, Brian Giera, Adam T. Moody, T. Nathan Mundhenk, Brian Van Essen, Eric X. Wang, David P. Widemann, Qing Wu, William E. Murphy, Jamie K. Infantolino, James A. Ross, Dale R. Shires, Manuel M. Vindiola, Raju Namburu, Dharmendra S. Modha

Proceedings of the International Conference for High Performance Computing, 2016

2015

Visual saliency on networks of neurosynaptic cores.

Alexander Andreopoulos, Brian Taba, Andrew S. Cassidy, Rodrigo Alvarez-Icaza, Myron Flickner, William P. Risk, Arnon Amir, Paul Merolla, John V. Arthur, David J. Berg, Jeffrey A. Kusnitz, Pallab Datta, Steven K. Esser, Rathinakumar Appuswamy, Davis Barch, Dharmendra S. Modha

IBM J. Res. Dev., 2015

Backpropagation for Energy-Efficient Neuromorphic Computing.

Steven K. Esser, Rathinakumar Appuswamy, Paul Merolla, John V. Arthur, Dharmendra S. Modha

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Computing Linear Functions by Linear Coding Over Networks.

Rathinakumar Appuswamy, Massimo Franceschetti

IEEE Trans. Inf. Theory, 2014

Real-Time Scalable Cortical Computing at 46 Giga-Synaptic OPS/Watt with ~100× Speedup in Time-to-Solution and ~100, 000× Reduction in Energy-to-Solution.

Andrew S. Cassidy, Rodrigo Alvarez-Icaza, Filipp Akopyan, Jun Sawada, John V. Arthur, Paul Merolla, Pallab Datta, Marc González Tallada, Brian Taba, Alexander Andreopoulos, Arnon Amir, Steven K. Esser, Jeff Kusnitz, Rathinakumar Appuswamy, Chuck Haymes, Bernard Brezzo, Roger Moussalli, Ralph Bellofatto, Christian W. Baks, Michael Mastro, Kai Schleupen, Charles E. Cox, Ken Inoue, Steven E. Millman, Nabil Imam, Emmett McQuinn, Yutaka Y. Nakamura, Ivan Vo, Chen Guok, Don Nguyen, Scott Lekuch, Sameh W. Asaad, Daniel J. Friedman, Bryan L. Jackson, Myron Flickner, William P. Risk, Rajit Manohar, Dharmendra S. Modha

Proceedings of the International Conference for High Performance Computing, 2014

2013

Linear Codes, Target Function Classes, and Network Computing Capacity.

Rathinakumar Appuswamy, Massimo Franceschetti, Nikhil Karamchandani, Kenneth Zeger

IEEE Trans. Inf. Theory, 2013

Cognitive computing systems: Algorithms and applications for networks of neurosynaptic cores.

Steven K. Esser, Alexander Andreopoulos, Rathinakumar Appuswamy, Pallab Datta, Davis Barch, Arnon Amir, John V. Arthur, Andrew Cassidy, Myron Flickner, Paul Merolla, Shyamal Chandra, Nicola Basilico, Stefano Carpin, Tom Zimmerman, Frank Zee, Rodrigo Alvarez-Icaza, Jeffrey A. Kusnitz, Theodore M. Wong, William P. Risk, Emmett McQuinn, Tapan K. Nayak, Raghavendra Singh, Dharmendra S. Modha

Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

2011

Network coding for function computation.

Rathinakumar Appuswamy

PhD thesis, 2011

Time and Energy Complexity of Function Computation Over Networks.

Nikhil Karamchandani, Rathinakumar Appuswamy, Massimo Franceschetti

IEEE Trans. Inf. Theory, 2011

Network Coding for Computing: Cut-Set Bounds.

Rathinakumar Appuswamy, Massimo Franceschetti, Nikhil Karamchandani, Kenneth Zeger

IEEE Trans. Inf. Theory, 2011

Network coding for computing: Linear codes

Rathinakumar Appuswamy, Massimo Franceschetti, Nikhil Karamchandani, Kenneth Zeger

CoRR, 2011

Linear coding for network computing.

Rathinakumar Appuswamy, Massimo Franceschetti, Nikhil Karamchandani, Kenneth Zeger

Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

2010

Computing linear functions with linear network codes.

Rathinakumar Appuswamy, Massimo Franceschetti

Proceedings of the 48th Annual Allerton Conference on Communication, 2010

2009

Network Coding for Computing Part I : Cut-Set Bounds

Rathinakumar Appuswamy, Massimo Franceschetti, Nikhil Karamchandani, Kenneth Zeger

CoRR, 2009

Distributed computation of symmetric functions with binary inputs.

Nikhil Karamchandani, Rathinakumar Appuswamy, Massimo Franceschetti

Proceedings of the 2009 IEEE Information Theory Workshop, 2009

Network computing capacity for the reverse butterfly network.

Rathinakumar Appuswamy, Massimo Franceschetti, Nikhil Karamchandani, Kenneth Zeger

Proceedings of the IEEE International Symposium on Information Theory, 2009

2008

Complete Mutually Orthogonal Golay Complementary Sets From Reed-Muller Codes.

Rathinakumar Appuswamy, Ajit Kumar Chaturvedi

IEEE Trans. Inf. Theory, 2008

Network coding for computing.

Rathinakumar Appuswamy, Massimo Franceschetti, Nikhil Karamchandani, Kenneth Zeger

Proceedings of the 46th Annual Allerton Conference on Communication, 2008

2006

QoS guarantee and provisioning for realtime digital video over mobile ad hoc cdma networks with cross-layer design.

Qi Qu, Rathinakumar Appuswamy, Yee Sin Chan

IEEE Wirel. Commun., 2006

A New Framework for Constructing Mutually Orthogonal Complementary Sets and ZCZ Sequences.

Rathinakumar Appuswamy, Ajit Kumar Chaturvedi

IEEE Trans. Inf. Theory, 2006

Optimality of Linear Codes for Broadcast-Mode Multicast Networks.

Rathinakumar Appuswamy, Massimo Franceschetti, Kenneth Zeger

Proceedings of the Proceedings 2006 IEEE International Symposium on Information Theory, 2006

2000

Implementation Issues In ERP.

Rathinakumar Appuswamy

Proceedings of the ICSTM2000, 2000