Implementation of signal processing tasks on neuromorphic hardware

Because of power and reliability issues, computer architects are forced to explore new types of architectures, such as heterogeneous systems embedding hardware accelerators. Neuromorphic systems are good candidate accelerators that can perform efficient and robust computing for certain classes of ap...

Full description

Saved in:
Bibliographic Details
Published inThe 2011 International Joint Conference on Neural Networks pp. 1120 - 1125
Main Authors Temam, O., Heliot, R.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2011
Subjects
Bismuth
Joints
Neural networks
USA Councils
Online AccessGet full text

Cover

More Information
Summary:Because of power and reliability issues, computer architects are forced to explore new types of architectures, such as heterogeneous systems embedding hardware accelerators. Neuromorphic systems are good candidate accelerators that can perform efficient and robust computing for certain classes of applications. We propose a piking neurons based accelerator, with its hardware and software, that can be easily programmed to execute a wide range of signal processing applications. A library of operators is built to facilitate implementation of various types of applications. Automated placement and routing software tools are used to map these applications onto the hardware. Altogether, this system aims at providing to the user a simple way to implement signal processing tasks on neuromorphic hardware.
ISBN:1424496357
9781424496358
ISSN:2161-4393
2161-4407
DOI:10.1109/IJCNN.2011.6033349