An improved CNN algorithm for accelerating structural optimization with pulsating array

ZhiLiang Xiao

doi:10.1117/12.2671338

16 March 2023 An improved CNN algorithm for accelerating structural optimization with pulsating array

ZhiLiang Xiao

Proceedings Volume 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022); 125930K (2023) https://doi.org/10.1117/12.2671338
Event: 2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 2022, Guangzhou, China

Abstract

The rapid development of artificial intelligence has prompted the convolutional neural network (CNN) to process huge amount of data, which has caused a great burden on convolution operations. Therefore, according to the characteristics of the systolic array architecture, the acceleration structure of CNN is constructed by fusing it with CNN. Besides, it is optimized in practical application, and its effectiveness is verified. The experimental results show that in the broadcast architecture, the time required by the CNN acceleration architecture is at least 0.005, while the maximum throughput is 16.83, which is far higher than the acceleration architecture under the systolic array architecture. In the case of small change in the maximum frequency, the error rate is the same as that of the systolic array, which is about 3.62%. In the comparison of various methods proposed on the systolic array, the accuracy rate of CNN acceleration architecture is 94.7%, and the utilization rate is 81.95%. The correctness and effectiveness of the algorithm are proved. To sum up, the improved CNN acceleration structure based on pulse array optimization reduces the response time and meets the requirements of terminal calculation force, which is of high significance in practical application

Citation Download Citation

ZhiLiang Xiao "An improved CNN algorithm for accelerating structural optimization with pulsating array", Proc. SPIE 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 125930K (16 March 2023); https://doi.org/10.1117/12.2671338

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