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This content will become publicly available on March 18, 2017

Title: A Survey of Techniques for Approximate Computing

Approximate computing trades off computation quality with the effort expended and as rising performance demands confront with plateauing resource budgets, approximate computing has become, not merely attractive, but even imperative. Here, 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 etc., and programming frameworks for AC. Moreover, we classify these techniques based on several key characteristics to emphasize their similarities and differences. Finally, the aim of this paper 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.
Authors:
 [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
OSTI Identifier:
1286958
Grant/Contract Number:
AC05-00OR22725
Type:
Accepted Manuscript
Journal Name:
ACM Computing Surveys
Additional Journal Information:
Journal Volume: 48; Journal Issue: 4; Journal ID: ISSN 0360-0300
Publisher:
Association for Computing Machinery (ACM)
Research Org:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING review; classification; approximate computing technique (ACT); approximate storage; quality configurability; CPU; GPU; FPGA; neural networks; design; performance