Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Filipp Akopyan"'
Autor:
Peter J. Carlson, Michael DeBole, John V. Arthur, Myron D. Flickner, Scott Lekuch, Jeffrey L. McKinstry, Andrew S. Cassidy, Michael Mastro, Jeff Kusnitz, Brian Taba, Carmelo di Nolfo, Rathinakumar Appuswamy, Jun Sawada, Steven K. Esser, Pallab Datta, Brent Paulovicks, Klamo Jennifer, Kai Schleupen, Kevin L. Holland, Arnon Amir, Guillaume J. Garreau, Filipp Akopyan, Dharmendra S. Modha, Benjamin G. Shaw, Alexander Andreopoulos, Tapan K. Nayak, Carlos Tadeo Ortega Otero, William P. Risk
Publikováno v:
Computer. 52:20-29
IBM's brain-inspired processor is a massively parallel neural network inference engine containing 1 million spiking neurons and 256 million low-precision synapses. Now, after a decade of fundamental research spanning neuroscience, architecture, chips
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49b898399142d35f409e1c3c3bdb2c8b
https://doi.org/10.1109/mc.2019.2903009
https://doi.org/10.1109/mc.2019.2903009
Autor:
Bryan L. Jackson, Rajit Manohar, Andrew S. Cassidy, Brian Taba, Gi-Joon Nam, Paul A. Merolla, Rodrigo Alvarez-Icaza, William P. Risk, Jente B. Kuang, Pallab Datta, Filipp Akopyan, Michael P. Beakes, John V. Arthur, Nabil Imam, Bernard Brezzo, Yutaka Nakamura, Dharmendra S. Modha, Jun Sawada
Publikováno v:
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 34:1537-1557
The new era of cognitive computing brings forth the grand challenge of developing systems capable of processing massive amounts of noisy multisensory data. This type of intelligent computing poses a set of constraints, including real-time operation,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c4608c0c8298c2492f7d58bbe0cd2a77
https://doi.org/10.1109/tcad.2015.2474396
https://doi.org/10.1109/tcad.2015.2474396
Autor:
Bryan L. Jackson, Filipp Akopyan, Andrew S. Cassidy, Arnon Amir, Rodrigo Alvarez-Icaza, Rajit Manohar, Steven K. Esser, Paul A. Merolla, John V. Arthur, Myron D. Flickner, Dharmendra S. Modha, Jun Sawada, Yutaka Nakamura, William P. Risk, Ivan Vo, Bernard Brezzo, Rathinakumar Appuswamy, Brian Taba, Nabil Imam, Chen Guo
Publikováno v:
Science. 345:668-673
Modeling computer chips on real brains Computers are nowhere near as versatile as our own brains. Merolla et al. applied our present knowledge of the structure and function of the brain to design a new computer chip that uses the same wiring rules an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ddea8d132ab672af1b9c3e153f9189a8
https://doi.org/10.1126/science.1254642
https://doi.org/10.1126/science.1254642
Autor:
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 Shaw, Hayley Wu, Brian Giera, Adam T. Moody, Nathan Mundhenk, Brian C. 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
Publikováno v:
SC16: International Conference for High Performance Computing, Networking, Storage and Analysis.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4eb353a85553254286eef8f2d979b3c7
https://doi.org/10.1109/sc.2016.11
https://doi.org/10.1109/sc.2016.11
Autor:
Filipp Akopyan
Publikováno v:
ISPD
Developing scalable real-time systems that can simultaneously process massive amounts of noisy multi-sensory data, while being energy efficient, is a dominant challenge in the new era of cognitive computing. Low-power, flexible neurosynaptic architec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3047c1214693b63658333f68f92636eb
https://doi.org/10.1145/2872334.2878629
https://doi.org/10.1145/2872334.2878629
Autor:
Rathinakumar Appuswamy, Roger Moussalli, Rajit Manohar, Emmett McQuinn, Andrew S. Cassidy, Christian W. Baks, Paul A. Merolla, Filipp Akopyan, John V. Arthur, Myron D. Flickner, Scott Lekuch, Michael Mastro, Brian Taba, Don Nguyen, Yutaka Nakamura, Sameh W. Asaad, Rodrigo Alvarez-Icaza, C. Haymes, Ken Inoue, Arnon Amir, Marc Gonzalez Tallada, Alexander Andreopoulos, Kai Schleupen, Steve Millman, Daniel Friedman, Steven K. Esser, Jeff Kusnitz, Jun Sawada, Ivan Vo, Bryan L. Jackson, Nabil Imam, Chen Guok, Charles Edwin Cox, Pallab Datta, Bernard Brezzo, Ralph Bellofatto, Dharmendra S. Modha, William P. Risk
Publikováno v:
SC
Drawing on neuroscience, we have developed a parallel, event-driven kernel for neurosynaptic computation, that is efficient with respect to computation, memory, and communication. Building on the previously demonstrated highly optimized software expr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c6563133b16300ac2feb5a7fcb2b374a
https://doi.org/10.1109/sc.2014.8
https://doi.org/10.1109/sc.2014.8
Autor:
Paul A, Merolla, John V, Arthur, Rodrigo, Alvarez-Icaza, Andrew S, Cassidy, Jun, Sawada, Filipp, Akopyan, Bryan L, Jackson, Nabil, Imam, Chen, Guo, Yutaka, Nakamura, Bernard, Brezzo, Ivan, Vo, Steven K, Esser, Rathinakumar, Appuswamy, Brian, Taba, Arnon, Amir, Myron D, Flickner, William P, Risk, Rajit, Manohar, Dharmendra S, Modha
Publikováno v:
Science (New York, N.Y.). 345(6197)
Inspired by the brain's structure, we have developed an efficient, scalable, and flexible non-von Neumann architecture that leverages contemporary silicon technology. To demonstrate, we built a 5.4-billion-transistor chip with 4096 neurosynaptic core
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::ff3b4f0788916d4da43b50530d3f8079
https://pubmed.ncbi.nlm.nih.gov/25104367
https://pubmed.ncbi.nlm.nih.gov/25104367
Autor:
Bryan L. Jackson, Steve K. Esser, William P. Risk, Emmett McQuinn, Daniel D Ben Dayan Rubin, Pallab Datta, Dharmendra S. Modha, Jun Sawada, John V. Arthur, Paul A. Merolla, Vitaly Feldman, Theodore M. Wong, Filipp Akopyan, Rodrigo Alvarez-Icaza, Arnon Amir, Andrew S. Cassidy
Publikováno v:
IJCNN
Marching along the DARPA SyNAPSE roadmap, IBM unveils a trilogy of innovations towards the TrueNorth cognitive computing system inspired by the brain's function and efficiency. Judiciously balancing the dual objectives of functional capability and im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::154c4f3444b06b7cfcc701b0af619032
https://doi.org/10.1109/ijcnn.2013.6707077
https://doi.org/10.1109/ijcnn.2013.6707077
Autor:
Andrew S. Cassidy, Shyamal Suhana Chandra, Rajit Manohar, Dharmendra S. Modha, Filipp Akopyan, William P. Risk, Rodrigo Alvarez, Steven K. Esser, Paul A. Merolla, John V. Arthur, Daniel D Ben Dayan Rubin, Nabil Imam
Publikováno v:
IJCNN
The grand challenge of neuromorphic computation is to develop a flexible brain-inspired architecture capable of a wide array of real-time applications, while striving towards the ultra-low power consumption and compact size of biological neural syste
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f040dc892d52ad10c6121f88ed3a831
https://zenodo.org/record/1273325
https://zenodo.org/record/1273325
Autor:
Filipp Akopyan, John V. Arthur, Paul A. Merolla, Nabil Imam, Dharmendra S. Modha, Rajit Manohar
Publikováno v:
ASYNC
We design and implement a key building block of a scalable neuromorphic architecture capable of running spiking neural networks in compact and low-power hardware. Our innovation is a configurable neurosynaptic core that combines 256 integrate-and-fir
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4ee9d3c9b9da706f2c8844ca0caad4f
https://doi.org/10.1109/async.2012.12
https://doi.org/10.1109/async.2012.12