.png){kind=icon}
返回
Profile-Based Output Error Compensation for Approximate Arithmetic Circuits
.png){kind=icon}
OA
AI
DOI：10.1109/TCSI.2020.2996567.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Truncation is one of the most commonly used approaches for circuit-level approximate computing. This paper proposes a scheme for error compensation of arithmetic circuits in which a so-called padding is utilized to compensate at the output for the truncated bits of the input operands. Compensation relies on adjusting the output results of an arithmetic circuit; the padding takes a value determined by utilizing statistical information based on profiling an arithmetic circuit to reduce the average signed difference between the inexact and exact values and so the mean square error. An extensive analysis and simulation-based evaluation of error metrics are performed on signed truncated adders, multipliers and dividers; an excellent agreement is found. Additional design metrics such as power consumption and circuit complexity are also assessed. Different applications of approximate arithmetic circuits with the proposed output error compensation scheme are presented. Matrix multiplication and image processing (changing detection) are investigated to show the effectiveness of the scheme proposed in this paper.
Keyword:
Error compensation
Adders
Computer architecture
Microprocessors
Complexity theory
Logic gates
Measurement
Approximate computing
arithmetic errors
computer arithmetic
error compensation
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.2
论文数:
9.7K
被引数:
2.2W
机构
引用论文
分享收藏A Retrospective and Prospective View of Approximate Computing [Point of View}.png)
PROCEEDINGS OF THE IEEEOAAI
PROCEEDINGS OF THE IEEEIF25.9
OAAI分享收藏A Majority-Based Imprecise Multiplier for Ultra-Efficient Approximate Image Multiplication用于超高效近似图像乘法的基于多数的不精确乘法器
PREAI
分享收藏
查看更多内容