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Accuracy Scalable Approximate Divider Based on Restoring Division for Energy Efficiency
| Content Provider | MDPI |
|---|---|
| Author | Jeong, Jonghyun Kim, Youngmin |
| Copyright Year | 2020 |
| Description | Approximate computing can considerably improve energy efficiency by mitigating the accuracy requirements of calculations in error resilient application programming, such as machine learning, audio–video signal processing, data mining, and search engines. In this study, we propose an approximate divider for dynamic energy-quality scaling, which involves a trade-off between accuracy and latency. Previous approximate dividers for dynamic energy-quality scaling are well-configured, but lack energy-quality scalability. The key is to create a more accurate dynamic approximate divider while extending the limits of accuracy to maximize energy efficiency and meet various accuracy requirements. The proposed divider, called the accuracy scalable approximate divider based on restoring division (ASAD-RD), uses restoring division to significantly improve the error of the approximate divider and to use less latency. For the 8-bit division, SAADI, the previous design, has an average accuracy of 90.78% to 98.77%; however, ASAD-RD can improve the accuracy between 95.2% and 99.23% and hardly requires additional power consumption. Furthermore, for the same target accuracy, ASAD-RD requires fewer cycle iterations than SAADI. Thus, ASAD-RD requires lower energy than SAADI and can operate as an energy-efficient approximate divider. |
| Starting Page | 31 |
| e-ISSN | 20799292 |
| DOI | 10.3390/electronics10010031 |
| Journal | Electronics |
| Issue Number | 1 |
| Volume Number | 10 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2020-12-28 |
| Access Restriction | Open |
| Subject Keyword | Electronics Hardware and Architecturee Approximate Computing Divider Energy Efficiency Energy Quality Scalability Restoring Division |
| Content Type | Text |
| Resource Type | Article |
