2009 - ACM Gordon Bell Prize The Cat is Out of the Bag: Cortical Simulations with 109 Neurons, 1013 Synapses
Dharmendra S. Modha mostly deals with TrueNorth, Parallel computing, Neuromorphic engineering, Cluster analysis and Synapse. His TrueNorth research incorporates themes from Frame, Pixel, Chip, Von Neumann architecture and Cognitive computing. His study in the field of Cache also crosses realms of Throughput.
His Neuromorphic engineering study incorporates themes from Scalability, Computer hardware, Static random-access memory and Spiking neural network. His Cluster analysis study integrates concerns from other disciplines, such as Disjoint sets, Algorithm, Set and Pattern recognition. The concepts of his Synapse study are interwoven with issues in Theoretical computer science, Neuron, Dendrite and Topology.
His primary areas of investigation include Computer hardware, Artificial neural network, Artificial intelligence, Neuromorphic engineering and Electronic circuit. Dharmendra S. Modha combines subjects such as Set, Electronic engineering, Core and Spiking neural network with his study of Computer hardware. His studies in Artificial neural network integrate themes in fields like Substrate, Inference, Neuron and Parallel computing.
His Artificial intelligence study combines topics in areas such as Machine learning, Computer vision and Pattern recognition. His research in Neuromorphic engineering is mostly focused on TrueNorth. His research in TrueNorth focuses on subjects like Scalability, which are connected to Computer architecture.
Dharmendra S. Modha mainly focuses on Artificial neural network, Artificial intelligence, Computer hardware, Algorithm and TrueNorth. His study in Artificial neural network is interdisciplinary in nature, drawing from both Substrate, Inference, Neuron, Parallel computing and Topology. His Artificial intelligence research integrates issues from Sequence, Computer vision and Pattern recognition.
His research integrates issues of Routing, Hardware software, Multi-core processor and Asynchronous communication in his study of Computer hardware. His Quantization and Error detection and correction study in the realm of Algorithm connects with subjects such as Sequence and Quantization. His study on TrueNorth is covered under Neuromorphic engineering.
His scientific interests lie mostly in TrueNorth, Artificial intelligence, Algorithm, Quantization and Neuromorphic engineering. Dharmendra S. Modha has researched TrueNorth in several fields, including Feature extraction, Computer architecture and Massively parallel, Parallel computing. His Parallel computing study integrates concerns from other disciplines, such as Telecommunications network, Backpropagation and Efficient energy use.
He has included themes like Latency and Computer vision in his Artificial intelligence study. His Algorithm research includes elements of Dimension and Robustness. The study incorporates disciplines such as Boltzmann machine, Very-large-scale integration, Markov process and Electronic design automation in addition to Neuromorphic engineering.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
A million spiking-neuron integrated circuit with a scalable communication network and interface
Paul A. Merolla;John V. Arthur;Rodrigo Alvarez-Icaza;Andrew S. Cassidy.
Concept Decompositions for Large Sparse Text Data Using Clustering
Inderjit S. Dhillon;Dharmendra S. Modha.
Machine Learning (2001)
Inderjit S. Dhillon;Subramanyam Mallela;Dharmendra S. Modha.
knowledge discovery and data mining (2003)
ARC: a self-tuning, low overhead replacement cache
Nimrod Megiddo;Dharmendra S. Modha.
file and storage technologies (2003)
A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation
Arindam Banerjee;Inderjit Dhillon;Joydeep Ghosh;Srujana Merugu.
Journal of Machine Learning Research (2007)
TrueNorth: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip
Filipp Akopyan;Jun Sawada;Andrew Cassidy;Rodrigo Alvarez-Icaza.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2015)
Convolutional networks for fast, energy-efficient neuromorphic computing
Steven K. Esser;Paul A. Merolla;John V. Arthur;Andrew S. Cassidy.
Proceedings of the National Academy of Sciences of the United States of America (2016)
Backpropagation for energy-efficient neuromorphic computing
Steve K. Esser;Rathinakumar Appuswamy;Paul A. Merolla;John V. Arthur.
neural information processing systems (2015)
A Data-Clustering Algorithm on Distributed Memory Multiprocessors
Inderjit S. Dhillon;Dharmendra S. Modha.
knowledge discovery and data mining (1999)
A digital neurosynaptic core using embedded crossbar memory with 45pJ per spike in 45nm
Paul Merolla;John Arthur;Filipp Akopyan;Nabil Imam.
custom integrated circuits conference (2011)
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