The Progress in Application-Specific Integrated Circuit Design

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Circuit and Signal Processing".

Deadline for manuscript submissions: closed (15 February 2025) | Viewed by 956

Special Issue Editors


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Guest Editor
1. University of Chinese Academy of Sciences, Beijing 100049, China
2. Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000, China
Interests: ASICs and sensors

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Guest Editor
School of Astronautics, Harbin Institute of Technology, Harbin 150001, China
Interests: mixed-signal analog IC design
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000, China
Interests: pixel sensor and digital ASICs

Special Issue Information

Dear Colleagues,

Application-Specific Integrated Circuits (ASICs) are custom-designed integrated circuits tailored to meet the needs of specific applications. They represent the cutting-edge applications of semiconductor technology. Optimized for particular tasks, ASICs can offer higher performance, lower power consumption, and cost-effectiveness while reducing the overall complexity of systems. This specialized nature makes ASICs crucial in critical areas such as high-performance computing, mobile communications, digital media, automotive electronics, and medical devices. ASICs are an indispensable part of modern electronic systems. They drive technological progress and greatly enrich and facilitate people's daily lives.

This Special Issue aims to collect original research articles on Progress in Application-Specific Integrated Circuit Design. The topics of interest for this Special Issue include, but are not limited to, the following:

  • Frontiers of Process Technology;
  • Expansion into Application Fields;
  • Design Methods and Tools;
  • System Integration technology;
  • New Materials and Devices;
  • ASIC Design for Emerging Technologies;
  • Sensor and Actuator Interfaces;
  • Reliability and Fault Tolerance;
  • Sustainability and Green ASICs;
  • Market Analysis, Future Outlook and Challenges.

Prof. Dr. Chengxin Zhao
Dr. Yongsheng Wang
Dr. Xiaoyang Niu
Guest Editors

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Keywords

  • application-specific integrated circuits (ASICs)
  • AI acceleration
  • energy efficiency
  • manufacturability
  • reliability engineering
  • emerging technologies
  • new application fields
  • new materials and devices
  • design methods and tools
  • integration technology

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Published Papers (1 paper)

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Research

9 pages, 520 KiB  
Article
Research on Approximate Computation of Signal Processing Algorithms for AIoT Processors Based on Deep Learning
by Yingzhe Liu, Fangfa Fu and Xuejian Sun
Electronics 2025, 14(6), 1064; https://doi.org/10.3390/electronics14061064 - 7 Mar 2025
Viewed by 525
Abstract
In the post-Moore era, the excessive amount of information brings great challenges to the performance of computing systems. To cope with these challenges, approximate computation has developed rapidly, which enhances the system performance with minor degradation in accuracy. In this paper, we investigate [...] Read more.
In the post-Moore era, the excessive amount of information brings great challenges to the performance of computing systems. To cope with these challenges, approximate computation has developed rapidly, which enhances the system performance with minor degradation in accuracy. In this paper, we investigate the utilization of an Artificial Intelligence of Things (AIoT) processor for approximate computing. Firstly, we employed neural architecture search (NAS) to acquire the neural network structure for approximate computation, which approximates the functions of FFT, DCT, FIR, and IIR. Subsequently, based on this structure, we quantized and trained a neural network implemented on the AI accelerator of the MAX78000 development board. To evaluate the performance, we implemented the same functions using the CMSIS-DSP library. The results demonstrate that the computational efficiency of the approximate computation on the AI accelerator is significantly higher compared to traditional DSP implementations. Therefore, the approximate computation based on AIoT devices can be effectively utilized in real-time applications. Full article
(This article belongs to the Special Issue The Progress in Application-Specific Integrated Circuit Design)
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