Design of Approximate Booth Squarer for Error-Tolerant Computing
To explore the benefits of approximate computing, this article proposes an approximate partial product generator for squarer (APPGS). Using APPGS, three designs of approximate radix-4 Booth squarers (ABS1, ABS2, and ABS3) are proposed. APPGS produces approximate partial products in r number of lea...
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Veröffentlicht in: | IEEE transactions on very large scale integration (VLSI) systems 2020-05, Vol.28 (5), p.1230-1241 |
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description | To explore the benefits of approximate computing, this article proposes an approximate partial product generator for squarer (APPGS). Using APPGS, three designs of approximate radix-4 Booth squarers (ABS1, ABS2, and ABS3) are proposed. APPGS produces approximate partial products in r number of least significant columns of the partial product matrix. ABS2 and ABS3 utilize approximate adders and compressors with a novel input signal rearrangement method for the accumulation of approximate partial products. Moreover, the ABS3 features an error recovery module at k number of most significant columns of the approximate partial products. The proposed squarers with different values of r and k are simulated using 45-nm CMOS technology. The results indicate that the proposed squarers achieve optimized performance for both hardware and accuracy metrics. Compared to the exact Booth squarer, the 16-bit ABS1 with r=16 achieves a reduction of 13.6%, 22.2%, and 13.7% in power, delay, and area, respectively, with a normalized mean error distance (NMED) of 4.6\times 10^{-6} . The ABS2 has power, delay, and area savings of 25.8%, 33.8%, and 19.8%, respectively, with an NMED of 7.2\times 10^{-6} . The ABS3 with k=6 has 18.5% reduction in power, 29.4% reduction in delay, and 16.9% reduction in area with an NMED of 0.56\times 10^{-6} . The performance of the proposed squarers is evaluated with a telecommunication application, where the ABS3 with k=6 produces an output signal with a signal-to-noise ratio of 32.45 dB. |
doi_str_mv | 10.1109/TVLSI.2020.2976131 |
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H. ; Nithin Kumar, Y. B. ; Dwivedi, Devesh</creator><creatorcontrib>Manikantta Reddy, K. ; Vasantha, M. H. ; Nithin Kumar, Y. B. ; Dwivedi, Devesh</creatorcontrib><description><![CDATA[To explore the benefits of approximate computing, this article proposes an approximate partial product generator for squarer (APPGS). Using APPGS, three designs of approximate radix-4 Booth squarers (ABS1, ABS2, and ABS3) are proposed. APPGS produces approximate partial products in <inline-formula> <tex-math notation="LaTeX">r </tex-math></inline-formula> number of least significant columns of the partial product matrix. ABS2 and ABS3 utilize approximate adders and compressors with a novel input signal rearrangement method for the accumulation of approximate partial products. Moreover, the ABS3 features an error recovery module at <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula> number of most significant columns of the approximate partial products. The proposed squarers with different values of <inline-formula> <tex-math notation="LaTeX">r </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula> are simulated using 45-nm CMOS technology. The results indicate that the proposed squarers achieve optimized performance for both hardware and accuracy metrics. Compared to the exact Booth squarer, the 16-bit ABS1 with <inline-formula> <tex-math notation="LaTeX">r=16 </tex-math></inline-formula> achieves a reduction of 13.6%, 22.2%, and 13.7% in power, delay, and area, respectively, with a normalized mean error distance (NMED) of <inline-formula> <tex-math notation="LaTeX">4.6\times 10^{-6} </tex-math></inline-formula>. The ABS2 has power, delay, and area savings of 25.8%, 33.8%, and 19.8%, respectively, with an NMED of <inline-formula> <tex-math notation="LaTeX">7.2\times 10^{-6} </tex-math></inline-formula>. The ABS3 with <inline-formula> <tex-math notation="LaTeX">k=6 </tex-math></inline-formula> has 18.5% reduction in power, 29.4% reduction in delay, and 16.9% reduction in area with an NMED of <inline-formula> <tex-math notation="LaTeX">0.56\times 10^{-6} </tex-math></inline-formula>. The performance of the proposed squarers is evaluated with a telecommunication application, where the ABS3 with <inline-formula> <tex-math notation="LaTeX">k=6 </tex-math></inline-formula> produces an output signal with a signal-to-noise ratio of 32.45 dB.]]></description><identifier>ISSN: 1063-8210</identifier><identifier>EISSN: 1557-9999</identifier><identifier>DOI: 10.1109/TVLSI.2020.2976131</identifier><identifier>CODEN: IEVSE9</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Adders ; Approximate Booth squarer ; approximate computing ; approximate partial product generator for squarer (APPGS) ; CMOS ; Complexity theory ; Compressors ; Computation ; Computer simulation ; Delay ; Delays ; Encoding ; Error recovery ; Generators ; Hardware ; input signal rearrangement (ISR) ; Noise levels ; signal probability ; Signal to noise ratio</subject><ispartof>IEEE transactions on very large scale integration (VLSI) systems, 2020-05, Vol.28 (5), p.1230-1241</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c295t-e98ddab9a3813a5cbdcc604040dff48d5f66219bc7c3382cdfd2027999858c2e3</citedby><cites>FETCH-LOGICAL-c295t-e98ddab9a3813a5cbdcc604040dff48d5f66219bc7c3382cdfd2027999858c2e3</cites><orcidid>0000-0002-2205-1568</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9025773$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54736</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9025773$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Manikantta Reddy, K.</creatorcontrib><creatorcontrib>Vasantha, M. H.</creatorcontrib><creatorcontrib>Nithin Kumar, Y. B.</creatorcontrib><creatorcontrib>Dwivedi, Devesh</creatorcontrib><title>Design of Approximate Booth Squarer for Error-Tolerant Computing</title><title>IEEE transactions on very large scale integration (VLSI) systems</title><addtitle>TVLSI</addtitle><description><![CDATA[To explore the benefits of approximate computing, this article proposes an approximate partial product generator for squarer (APPGS). Using APPGS, three designs of approximate radix-4 Booth squarers (ABS1, ABS2, and ABS3) are proposed. APPGS produces approximate partial products in <inline-formula> <tex-math notation="LaTeX">r </tex-math></inline-formula> number of least significant columns of the partial product matrix. ABS2 and ABS3 utilize approximate adders and compressors with a novel input signal rearrangement method for the accumulation of approximate partial products. Moreover, the ABS3 features an error recovery module at <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula> number of most significant columns of the approximate partial products. The proposed squarers with different values of <inline-formula> <tex-math notation="LaTeX">r </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula> are simulated using 45-nm CMOS technology. The results indicate that the proposed squarers achieve optimized performance for both hardware and accuracy metrics. Compared to the exact Booth squarer, the 16-bit ABS1 with <inline-formula> <tex-math notation="LaTeX">r=16 </tex-math></inline-formula> achieves a reduction of 13.6%, 22.2%, and 13.7% in power, delay, and area, respectively, with a normalized mean error distance (NMED) of <inline-formula> <tex-math notation="LaTeX">4.6\times 10^{-6} </tex-math></inline-formula>. The ABS2 has power, delay, and area savings of 25.8%, 33.8%, and 19.8%, respectively, with an NMED of <inline-formula> <tex-math notation="LaTeX">7.2\times 10^{-6} </tex-math></inline-formula>. The ABS3 with <inline-formula> <tex-math notation="LaTeX">k=6 </tex-math></inline-formula> has 18.5% reduction in power, 29.4% reduction in delay, and 16.9% reduction in area with an NMED of <inline-formula> <tex-math notation="LaTeX">0.56\times 10^{-6} </tex-math></inline-formula>. The performance of the proposed squarers is evaluated with a telecommunication application, where the ABS3 with <inline-formula> <tex-math notation="LaTeX">k=6 </tex-math></inline-formula> produces an output signal with a signal-to-noise ratio of 32.45 dB.]]></description><subject>Adders</subject><subject>Approximate Booth squarer</subject><subject>approximate computing</subject><subject>approximate partial product generator for squarer (APPGS)</subject><subject>CMOS</subject><subject>Complexity theory</subject><subject>Compressors</subject><subject>Computation</subject><subject>Computer simulation</subject><subject>Delay</subject><subject>Delays</subject><subject>Encoding</subject><subject>Error recovery</subject><subject>Generators</subject><subject>Hardware</subject><subject>input signal rearrangement (ISR)</subject><subject>Noise levels</subject><subject>signal probability</subject><subject>Signal to noise ratio</subject><issn>1063-8210</issn><issn>1557-9999</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9UMtOAkEQnBhNRPQH9LKJ58V57LxuIqKSkHgAvU6GeeAS2FlmdhP9ewchdh-6D1XdVQXALYIjhKB8WH7OF7MRhhiOsOQMEXQGBohSXspc53mHjJQCI3gJrlLaQIiqSsIBeHx2qV43RfDFuG1j-K53unPFUwjdV7HY9zq6WPgQi2mMIZbLsHVRN10xCbu27-pmfQ0uvN4md3OaQ_DxMl1O3sr5--tsMp6XBkvalU4Ka_VKaiIQ0dSsrDEMVrmt95Ww1DOGkVwZbggR2FhvsxuexQsqDHZkCO6Pd7PIfe9Spzahj01-qTCRFLGKsyqj8BFlYkgpOq_amB3FH4WgOiSl_pJSh6TUKalMujuSaufcP0FCTDkn5Be6KWSy</recordid><startdate>20200501</startdate><enddate>20200501</enddate><creator>Manikantta Reddy, K.</creator><creator>Vasantha, M. H.</creator><creator>Nithin Kumar, Y. B.</creator><creator>Dwivedi, Devesh</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-2205-1568</orcidid></search><sort><creationdate>20200501</creationdate><title>Design of Approximate Booth Squarer for Error-Tolerant Computing</title><author>Manikantta Reddy, K. ; Vasantha, M. H. ; Nithin Kumar, Y. B. ; Dwivedi, Devesh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c295t-e98ddab9a3813a5cbdcc604040dff48d5f66219bc7c3382cdfd2027999858c2e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adders</topic><topic>Approximate Booth squarer</topic><topic>approximate computing</topic><topic>approximate partial product generator for squarer (APPGS)</topic><topic>CMOS</topic><topic>Complexity theory</topic><topic>Compressors</topic><topic>Computation</topic><topic>Computer simulation</topic><topic>Delay</topic><topic>Delays</topic><topic>Encoding</topic><topic>Error recovery</topic><topic>Generators</topic><topic>Hardware</topic><topic>input signal rearrangement (ISR)</topic><topic>Noise levels</topic><topic>signal probability</topic><topic>Signal to noise ratio</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Manikantta Reddy, K.</creatorcontrib><creatorcontrib>Vasantha, M. H.</creatorcontrib><creatorcontrib>Nithin Kumar, Y. B.</creatorcontrib><creatorcontrib>Dwivedi, Devesh</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on very large scale integration (VLSI) systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Manikantta Reddy, K.</au><au>Vasantha, M. H.</au><au>Nithin Kumar, Y. B.</au><au>Dwivedi, Devesh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Design of Approximate Booth Squarer for Error-Tolerant Computing</atitle><jtitle>IEEE transactions on very large scale integration (VLSI) systems</jtitle><stitle>TVLSI</stitle><date>2020-05-01</date><risdate>2020</risdate><volume>28</volume><issue>5</issue><spage>1230</spage><epage>1241</epage><pages>1230-1241</pages><issn>1063-8210</issn><eissn>1557-9999</eissn><coden>IEVSE9</coden><abstract><![CDATA[To explore the benefits of approximate computing, this article proposes an approximate partial product generator for squarer (APPGS). Using APPGS, three designs of approximate radix-4 Booth squarers (ABS1, ABS2, and ABS3) are proposed. APPGS produces approximate partial products in <inline-formula> <tex-math notation="LaTeX">r </tex-math></inline-formula> number of least significant columns of the partial product matrix. ABS2 and ABS3 utilize approximate adders and compressors with a novel input signal rearrangement method for the accumulation of approximate partial products. Moreover, the ABS3 features an error recovery module at <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula> number of most significant columns of the approximate partial products. The proposed squarers with different values of <inline-formula> <tex-math notation="LaTeX">r </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula> are simulated using 45-nm CMOS technology. The results indicate that the proposed squarers achieve optimized performance for both hardware and accuracy metrics. Compared to the exact Booth squarer, the 16-bit ABS1 with <inline-formula> <tex-math notation="LaTeX">r=16 </tex-math></inline-formula> achieves a reduction of 13.6%, 22.2%, and 13.7% in power, delay, and area, respectively, with a normalized mean error distance (NMED) of <inline-formula> <tex-math notation="LaTeX">4.6\times 10^{-6} </tex-math></inline-formula>. The ABS2 has power, delay, and area savings of 25.8%, 33.8%, and 19.8%, respectively, with an NMED of <inline-formula> <tex-math notation="LaTeX">7.2\times 10^{-6} </tex-math></inline-formula>. The ABS3 with <inline-formula> <tex-math notation="LaTeX">k=6 </tex-math></inline-formula> has 18.5% reduction in power, 29.4% reduction in delay, and 16.9% reduction in area with an NMED of <inline-formula> <tex-math notation="LaTeX">0.56\times 10^{-6} </tex-math></inline-formula>. The performance of the proposed squarers is evaluated with a telecommunication application, where the ABS3 with <inline-formula> <tex-math notation="LaTeX">k=6 </tex-math></inline-formula> produces an output signal with a signal-to-noise ratio of 32.45 dB.]]></abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TVLSI.2020.2976131</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-2205-1568</orcidid></addata></record> |
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subjects | Adders Approximate Booth squarer approximate computing approximate partial product generator for squarer (APPGS) CMOS Complexity theory Compressors Computation Computer simulation Delay Delays Encoding Error recovery Generators Hardware input signal rearrangement (ISR) Noise levels signal probability Signal to noise ratio |
title | Design of Approximate Booth Squarer for Error-Tolerant Computing |
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