Quality Control for Approximate Accelerators by Error Prediction

被引：21
作者：
Khudia, Daya Shanker [1 ]
Zamirai, Babak [2 ]
Samadi, Mehrzad [1 ]
Mahlke, Scott [3 ]
机构：
[1] Univ Michigan, Comp Sci & Engn, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Dept Comp Sci & Engn, Ann Arbor, MI 48109 USA
[3] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
来源：
IEEE DESIGN & TEST | 2016年 / 33卷 / 01期
基金：
美国国家科学基金会;
关键词：
Approximate computing; Neural Network; Prediction;
D O I：
10.1109/MDAT.2015.2501306
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
How to ensure the output quality is one of the most critical challenges in approximate computing. This paper presents an online quality management system in an approximate-accelerator-based computing environment that can effectively detect and correct large approximation errors. © 2013 IEEE.
引用
收藏
页码：43 / 51
页数：8
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