Bio-Inspired Massively-Parallel Computation

被引:1
|
作者
Furber, Steve [1 ]
机构
[1] Univ Manchester, Manchester, Lancs, England
来源
PARALLEL COMPUTING: ON THE ROAD TO EXASCALE | 2016年 / 27卷
基金
欧洲研究理事会; 英国工程与自然科学研究理事会;
关键词
Massively-parallel computation; neural networks; bio-inspired computing; SPINNAKER; NETWORK;
D O I
10.3233/978-1-61499-621-7-3
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The SpiNNaker (Spiking Neural Network Architecture) project will soon deliver a machine incorporating a million ARM processor cores for real-time modeling of large-scale spiking neural networks. Although the scale of the machine is in the realms of high-performance computing, the technology used to build the machine comes very much from the mobile embedded world, using small integer cores and Network-on-Chip communications both on and between chips. The full machine will use a total of 10 square meters of active silicon area with 57,600 routers using predominantly multicast algorithms to convey real-time spike information through a lightweight asynchronous packet-switched fabric. This paper presents the philosophy behind the machine, and the future prospects for systems with increased cognitive capabilities based on an increasing understanding of how biological brains process information.
引用
收藏
页码:3 / 10
页数:8
相关论文
共 50 条
  • [31] Designing Novel Photonic Devices by Bio-Inspired Computing
    da Silva Santos, Carlos Henrique
    Goncalves, Marcos Sergio
    Hernandez-Figueroa, Hugo Enrique
    IEEE PHOTONICS TECHNOLOGY LETTERS, 2010, 22 (15) : 1177 - 1179
  • [32] A Survey of Diverse Nature Bio-Inspired Computing Models
    Kotteeswaran, C.
    Rajesh, A.
    SECOND INTERNATIONAL CONFERENCE ON CURRENT TRENDS IN ENGINEERING AND TECHNOLOGY (ICCTET 2014), 2014, : 120 - 124
  • [33] Bio-inspired evolutionary method for cable trench problem
    Jeng, Don Jyh-Fu
    Kim, Ikno
    Watada, Junzo
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2007, 3 (01): : 111 - 118
  • [34] Application of bio-inspired optimization algorithms in food processing
    Sarkar, Tanmay
    Salauddin, Molla
    Mukherjee, Alok
    Shariati, Mohammad Ali
    Rebezov, Maksim
    Tretyak, Lyudmila
    Pateiro, Mirian
    Lorenzo, Jose M.
    CURRENT RESEARCH IN FOOD SCIENCE, 2022, 5 : 432 - 450
  • [35] Bio-inspired computation for big data fusion, storage, processing, learning and visualization: state of the art and future directions
    Torre-Bastida, Ana, I
    Diaz-de-Arcaya, Josu
    Osaba, Eneko
    Muhammad, Khan
    Camacho, David
    Del Ser, Javier
    NEURAL COMPUTING & APPLICATIONS, 2021,
  • [36] Heat production optimization using bio-inspired algorithms
    Wozniak, Marcin
    Ksiazek, Kamil
    Marciniec, Jakub
    Polap, Dawid
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2018, 76 : 185 - 201
  • [37] Bio-inspired machine learning: programmed death and replication
    Grabovsky, Andrey
    Vanchurin, Vitaly
    NEURAL COMPUTING & APPLICATIONS, 2023, 35 (27) : 20273 - 20298
  • [38] On the optimization of fuzzy systems using bio-inspired strategies
    de Oliveira, JV
    1998 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AT THE IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE - PROCEEDINGS, VOL 1-2, 1998, : 1229 - 1234
  • [39] Bio-inspired machine learning: programmed death and replication
    Andrey Grabovsky
    Vitaly Vanchurin
    Neural Computing and Applications, 2023, 35 : 20273 - 20298
  • [40] Toward Human-Level Massively-Parallel Neural Networks with Hodgkin-Huxley Neurons
    Long, Lyle N.
    ARTIFICIAL GENERAL INTELLIGENCE (AGI 2016), 2016, 9782 : 314 - 323