Thumbnail
Access Restriction
Subscribed

Author Mittal, Sparsh
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2016
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword CPU ♦ FPGA ♦ GPU ♦ Review ♦ Approximate computing technique (ACT) ♦ Approximate storage ♦ Classification ♦ Neural networks ♦ Quality configurability
Abstract Approximate computing trades off computation quality with effort expended, and as rising performance demands confront plateauing resource budgets, approximate computing has become not merely attractive, but even imperative. In this article, we present a survey of techniques for approximate computing (AC). We discuss strategies for finding approximable program portions and monitoring output quality, techniques for using AC in different processing units (e.g., CPU, GPU, and FPGA), processor components, memory technologies, and so forth, as well as programming frameworks for AC. We classify these techniques based on several key characteristics to emphasize their similarities and differences. The aim of this article is to provide insights to researchers into working of AC techniques and inspire more efforts in this area to make AC the mainstream computing approach in future systems.
ISSN 03600300
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2016-03-01
Publisher Place New York
e-ISSN 15577341
Journal ACM Computing Surveys (CSUR)
Volume Number 48
Issue Number 4
Page Count 33
Starting Page 1
Ending Page 33


Open content in new tab

   Open content in new tab
Source: ACM Digital Library