Hardware-software partitioning for the design of system on chip by neural network optimization method

Zhongliang Pan; Wei Li; Qingyi Shao; Ling Chen

doi:10.1117/12.904816

15 November 2011 Hardware-software partitioning for the design of system on chip by neural network optimization method

Zhongliang Pan, Wei Li, Qingyi Shao, Ling Chen

Proceedings Volume 8321, Seventh International Symposium on Precision Engineering Measurements and Instrumentation; 83211T (2011) https://doi.org/10.1117/12.904816
Event: Seventh International Symposium on Precision Engineering Measurements and Instrumentation, 2011, Yunnan, China

Abstract

In the design procedure of system on chip (SoC), it is needed to make use of hardware-software co-design technique owing to the great complexity of SoC. One of main steps in hardware-software co-design is how to carry out the partitioning of a system into hardware and software components. The efficient approaches for hardware-software partitioning can achieve good system performance, which is superior to the techniques that use software only or use hardware only. In this paper, a method based on neural networks is presented for the hardware-software partitioning of system on chip. The discrete Hopfield neural networks corresponding to the problem of hardware-software partitioning is built, the states of neural neurons are able to represent whether the required components or functionalities are to be implemented in hardware or software. An algorithm based on the principle of simulated annealing is designed, which can be used to compute the minimal energy states of neural networks, therefore the optimal partitioning schemes are obtained. The experimental results show that the hardware-software partitioning method proposed in this paper can obtain the near optimal partitioning for a lot of example circuits.

Citation Download Citation

Zhongliang Pan, Wei Li, Qingyi Shao, and Ling Chen "Hardware-software partitioning for the design of system on chip by neural network optimization method", Proc. SPIE 8321, Seventh International Symposium on Precision Engineering Measurements and Instrumentation, 83211T (15 November 2011); https://doi.org/10.1117/12.904816

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available