Finding a Roadmap to achieve Large Neuromorphic Hardware Systems

Frontiers in Neuroscience

Jennifer eHasler¹  Harry Bo Marr² 

[1] Georgia Insitute of Technology;Raytheon;

关键词: neuromorphic engineering;    Cost of communication;    FPAA;    Reconfigurable Analog;    Silicon Neuron Implementation;    Simulink;   

DOI  :  10.3389/fnins.2013.00118

来源: DOAJ

【 摘 要 】

Neuromorphic systems are gaining increasing importance in an era where CMOS digital computing techniques are meeting hard physical limits. These silicon systems mimic extremely energy efficient neural computing structures, potentially both for solving engineering applications as well as understanding neural computation.Towards this end, the authors provide a glimpse at what the technology evolution roadmap looks like for these systems so that Neuromorphic engineers may gain the same benefit of anticipation and foresight that IC designers gained from Moore's law many years ago. Scaling of energy efficiency, performance, and size will be discussed as well as how the implementation and application space of Neuromorphic systems are expected to evolve over time.

【 授权许可】

Unknown