Zobrazeno 1 - 10
of 353
pro vyhledávání: '"Furber, Steve"'
Autor:
Yik, Jason, Berghe, Korneel Van den, Blanken, Douwe den, Bouhadjar, Younes, Fabre, Maxime, Hueber, Paul, Kleyko, Denis, Pacik-Nelson, Noah, Sun, Pao-Sheng Vincent, Tang, Guangzhi, Wang, Shenqi, Zhou, Biyan, Ahmed, Soikat Hasan, Joseph, George Vathakkattil, Leto, Benedetto, Micheli, Aurora, Mishra, Anurag Kumar, Lenz, Gregor, Sun, Tao, Ahmed, Zergham, Akl, Mahmoud, Anderson, Brian, Andreou, Andreas G., Bartolozzi, Chiara, Basu, Arindam, Bogdan, Petrut, Bohte, Sander, Buckley, Sonia, Cauwenberghs, Gert, Chicca, Elisabetta, Corradi, Federico, de Croon, Guido, Danielescu, Andreea, Daram, Anurag, Davies, Mike, Demirag, Yigit, Eshraghian, Jason, Fischer, Tobias, Forest, Jeremy, Fra, Vittorio, Furber, Steve, Furlong, P. Michael, Gilpin, William, Gilra, Aditya, Gonzalez, Hector A., Indiveri, Giacomo, Joshi, Siddharth, Karia, Vedant, Khacef, Lyes, Knight, James C., Kriener, Laura, Kubendran, Rajkumar, Kudithipudi, Dhireesha, Liu, Yao-Hong, Liu, Shih-Chii, Ma, Haoyuan, Manohar, Rajit, Margarit-Taulé, Josep Maria, Mayr, Christian, Michmizos, Konstantinos, Muir, Dylan, Neftci, Emre, Nowotny, Thomas, Ottati, Fabrizio, Ozcelikkale, Ayca, Panda, Priyadarshini, Park, Jongkil, Payvand, Melika, Pehle, Christian, Petrovici, Mihai A., Pierro, Alessandro, Posch, Christoph, Renner, Alpha, Sandamirskaya, Yulia, Schaefer, Clemens JS, van Schaik, André, Schemmel, Johannes, Schmidgall, Samuel, Schuman, Catherine, Seo, Jae-sun, Sheik, Sadique, Shrestha, Sumit Bam, Sifalakis, Manolis, Sironi, Amos, Stewart, Matthew, Stewart, Kenneth, Stewart, Terrence C., Stratmann, Philipp, Timcheck, Jonathan, Tömen, Nergis, Urgese, Gianvito, Verhelst, Marian, Vineyard, Craig M., Vogginger, Bernhard, Yousefzadeh, Amirreza, Zohora, Fatima Tuz, Frenkel, Charlotte, Reddi, Vijay Janapa
Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it difficult to accu
Externí odkaz:
http://arxiv.org/abs/2304.04640
This paper presents a new methodology to alleviate the fundamental trade-off between accuracy and latency in spiking neural networks (SNNs). The approach involves decoding confidence information over time from the SNN outputs and using it to develop
Externí odkaz:
http://arxiv.org/abs/2303.10276
Autor:
Xie, Shouyu, Jones, Edward, Zhang, Siru, Marsden, Edward, Baistow, Ian, Furber, Steve, Mitra, Srinjoy, Hamilton, Alister
Publikováno v:
In Neural Networks August 2024 176
Autor:
Christensen, Dennis V., Dittmann, Regina, Linares-Barranco, Bernabé, Sebastian, Abu, Gallo, Manuel Le, Redaelli, Andrea, Slesazeck, Stefan, Mikolajick, Thomas, Spiga, Sabina, Menzel, Stephan, Valov, Ilia, Milano, Gianluca, Ricciardi, Carlo, Liang, Shi-Jun, Miao, Feng, Lanza, Mario, Quill, Tyler J., Keene, Scott T., Salleo, Alberto, Grollier, Julie, Marković, Danijela, Mizrahi, Alice, Yao, Peng, Yang, J. Joshua, Indiveri, Giacomo, Strachan, John Paul, Datta, Suman, Vianello, Elisa, Valentian, Alexandre, Feldmann, Johannes, Li, Xuan, Pernice, Wolfram H. P., Bhaskaran, Harish, Furber, Steve, Neftci, Emre, Scherr, Franz, Maass, Wolfgang, Ramaswamy, Srikanth, Tapson, Jonathan, Panda, Priyadarshini, Kim, Youngeun, Tanaka, Gouhei, Thorpe, Simon, Bartolozzi, Chiara, Cleland, Thomas A., Posch, Christoph, Liu, Shih-Chii, Panuccio, Gabriella, Mahmud, Mufti, Mazumder, Arnab Neelim, Hosseini, Morteza, Mohsenin, Tinoosh, Donati, Elisa, Tolu, Silvia, Galeazzi, Roberto, Christensen, Martin Ejsing, Holm, Sune, Ielmini, Daniele, Pryds, N.
Publikováno v:
Neuromorph. Comput. Eng. 2 022501 (2022)
Modern computation based on the von Neumann architecture is today a mature cutting-edge science. In the Von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This dat
Externí odkaz:
http://arxiv.org/abs/2105.05956
Autor:
Höppner, Sebastian, Yan, Yexin, Dixius, Andreas, Scholze, Stefan, Partzsch, Johannes, Stolba, Marco, Kelber, Florian, Vogginger, Bernhard, Neumärker, Felix, Ellguth, Georg, Hartmann, Stephan, Schiefer, Stefan, Hocker, Thomas, Walter, Dennis, Liu, Genting, Garside, Jim, Furber, Steve, Mayr, Christian
This paper introduces the processing element architecture of the second generation SpiNNaker chip, implemented in 22nm FDSOI. On circuit level, the chip features adaptive body biasing for near-threshold operation, and dynamic voltage-and-frequency sc
Externí odkaz:
http://arxiv.org/abs/2103.08392
Autor:
Huang, Xiaoyu, Jones, Edward, Zhang, Siru, Xie, Shouyu, Furber, Steve, Goulermas, Yannis, Marsden, Edward, Baistow, Ian, Mitra, Srinjoy, Hamilton, Alister
This paper details the FPGA implementation methodology for Convolutional Spiking Neural Networks (CSNN) and applies this methodology to low-power radioisotope identification using high-resolution data. Power consumption of 75 mW has been achieved on
Externí odkaz:
http://arxiv.org/abs/2102.12565
Autor:
Huang, Xiaoyu, Jones, Edward, Zhang, Siru, Xie, Shouyu, Furber, Steve, Goulermas, Yannis, Marsden, Edward, Baistow, Ian, Mitra, Srinjoy, Hamilton, Alister
this paper presents a detailed methodology of a Spiking Neural Network (SNN) based low-power design for radioisotope identification. A low power cost of 72 mW has been achieved on FPGA with the inference accuracy of 100% at 10 cm test distance and 97
Externí odkaz:
http://arxiv.org/abs/2010.13125
Autor:
Chen, Runze, Li, Chen, Li, Yu, Miles, James J., Indiveri, Giacomo, Furber, Steve, Pavlidis, Vasilis F., Moutafis, Christoforos
Publikováno v:
Phys. Rev. Appl. 14, 014096 (2020)
Magnetic skyrmions have attracted considerable interest, especially after their recent experimental demonstration at room temperature in multilayers. The robustness, nanoscale size and non-volatility of skyrmions have triggered a substantial amount o
Externí odkaz:
http://arxiv.org/abs/2009.14462
Autor:
Yan, Yexin, Stewart, Terrence C., Choo, Xuan, Vogginger, Bernhard, Partzsch, Johannes, Hoeppner, Sebastian, Kelber, Florian, Eliasmith, Chris, Furber, Steve, Mayr, Christian
We implemented two neural network based benchmark tasks on a prototype chip of the second-generation SpiNNaker (SpiNNaker 2) neuromorphic system: keyword spotting and adaptive robotic control. Keyword spotting is commonly used in smart speakers to li
Externí odkaz:
http://arxiv.org/abs/2009.08921