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One of the most researched focuses is\n            <jats:italic>approximate computing (AC)<\/jats:italic>\n            . AC is a new computing paradigm in both hardware and software designs that aim to achieve energy-efficient digital systems. Although a variety of AC techniques have been studied so far, the main question,\n            <jats:italic>\u201cHow (in which section) can a program or a circuit be approximated?,\u201d<\/jats:italic>\n            has not been answered yet. This work addresses the above issue by developing a software framework Static Significance Analysis for Approximate Computing (SSA-AC) to analyze the target application program and guide the designers to identify parts of the program to which approximation can or cannot be applied. SSA-AC statically analyzes the significance of variables in the precise version of the program and thus needs no trial-and-error evaluation or specific test data. Experimental results show that SSA-AC can successfully extract the significance ranking of inputs\/variables to be approximated in much shorter time than existing statistical works that are inevitably data dependent.\n          <\/jats:p>","DOI":"10.1145\/3314575","type":"journal-article","created":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T18:38:37Z","timestamp":1554403117000},"page":"1-17","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["SSA-AC"],"prefix":"10.1145","volume":"24","author":[{"given":"Sara Ayman","family":"Metwalli","sequence":"first","affiliation":[{"name":"School of Engineering, Tokyo Institute of Technology, Japan"}]},{"given":"Yuko","family":"Hara-Azumi","sequence":"additional","affiliation":[{"name":"School of Engineering, Tokyo Institute of Technology, Japan"}]}],"member":"320","published-online":{"date-parts":[[2019,4,2]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Cesare Alippi. 2014. 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