Gennaro Di Meo;Gerardo Saggese;Antonio G. M. Strollo;Davide De Caro
{"title":"Approximate MAC Unit Using Static Segmentation","authors":"Gennaro Di Meo;Gerardo Saggese;Antonio G. M. Strollo;Davide De Caro","doi":"10.1109/TETC.2023.3315301","DOIUrl":null,"url":null,"abstract":"In this paper we investigate a novel approximate multiply-and-accumulate (MAC) unit, that computes \n<italic>Y</i>\n = \n<italic>A</i>\n × \n<italic>B</i>\n + \n<italic>C</i>\n using static segmentation. The proposed architecture uses a unique carry-propagate adder and performs segmentation on the three operands \n<italic>A</i>\n, \n<italic>B</i>\n, and \n<italic>C</i>\n, to reduce hardware cost. The circuit can be configured at design-time by two parameters. The first one controls the segmentation on \n<italic>A</i>\n and \n<italic>B</i>\n, while the second one controls the segmentation on \n<italic>C</i>\n and the adder length. An error compensation technique is also employed, to reduce the approximation error. Error analysis and implementation results in 28nm CMOS for 8-bits multiplier with 20-bits and 24-bits addition are presented. The proposed approximate MACs outperform the state of the art, showing the largest power saving when the mean relative error distance (\n<italic>MRED</i>\n) is larger than 2 × 10\n<sup>−3</sup>\n and 4 × 10\n<sup>−5</sup>\n for 20 and 24-bits addition, respectively. For \n<italic>MRED</i>\n of about 6 × 10\n<sup>−3</sup>\n the proposed approximate MAC with 20-bits addition exhibits a power reduction larger than 60% compared to the exact MAC and larger than 27% compared to the state-of-the-art approximate MACs. Application examples to image filtering and template matching show that proposed approximate circuits are good candidates in applications where their error performances are acceptable.","PeriodicalId":13156,"journal":{"name":"IEEE Transactions on Emerging Topics in Computing","volume":"12 4","pages":"968-979"},"PeriodicalIF":5.1000,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10258016","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Emerging Topics in Computing","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10258016/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper we investigate a novel approximate multiply-and-accumulate (MAC) unit, that computes
Y
=
A
×
B
+
C
using static segmentation. The proposed architecture uses a unique carry-propagate adder and performs segmentation on the three operands
A
,
B
, and
C
, to reduce hardware cost. The circuit can be configured at design-time by two parameters. The first one controls the segmentation on
A
and
B
, while the second one controls the segmentation on
C
and the adder length. An error compensation technique is also employed, to reduce the approximation error. Error analysis and implementation results in 28nm CMOS for 8-bits multiplier with 20-bits and 24-bits addition are presented. The proposed approximate MACs outperform the state of the art, showing the largest power saving when the mean relative error distance (
MRED
) is larger than 2 × 10
−3
and 4 × 10
−5
for 20 and 24-bits addition, respectively. For
MRED
of about 6 × 10
−3
the proposed approximate MAC with 20-bits addition exhibits a power reduction larger than 60% compared to the exact MAC and larger than 27% compared to the state-of-the-art approximate MACs. Application examples to image filtering and template matching show that proposed approximate circuits are good candidates in applications where their error performances are acceptable.
期刊介绍:
IEEE Transactions on Emerging Topics in Computing publishes papers on emerging aspects of computer science, computing technology, and computing applications not currently covered by other IEEE Computer Society Transactions. Some examples of emerging topics in computing include: IT for Green, Synthetic and organic computing structures and systems, Advanced analytics, Social/occupational computing, Location-based/client computer systems, Morphic computer design, Electronic game systems, & Health-care IT.