{"id":"https://openalex.org/W2400523863","doi":"https://doi.org/10.1145/2897937.2898042","title":"Low-power approximate convolution computing unit with domain-wall motion based \"spin-memristor\" for image processing applications","display_name":"Low-power approximate convolution computing unit with domain-wall motion based \"spin-memristor\" for image processing applications","publication_year":2016,"publication_date":"2016-05-25","ids":{"openalex":"https://openalex.org/W2400523863","doi":"https://doi.org/10.1145/2897937.2898042","mag":"2400523863"},"language":"en","primary_location":{"id":"doi:10.1145/2897937.2898042","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2897937.2898042","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/2897937.2898042","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 53rd Annual Design Automation Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/2897937.2898042","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015362699","display_name":"Yong Shim","orcid":"https://orcid.org/0000-0002-7101-6718"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yong Shim","raw_affiliation_strings":["Purdue University"],"affiliations":[{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032635465","display_name":"Abhronil Sengupta","orcid":"https://orcid.org/0000-0002-5545-4494"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abhronil Sengupta","raw_affiliation_strings":["Purdue University"],"affiliations":[{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031161187","display_name":"Kaushik Roy","orcid":"https://orcid.org/0009-0002-3375-2877"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaushik Roy","raw_affiliation_strings":["Purdue University"],"affiliations":[{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5015362699"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":2.2308,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.88687609,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11128","display_name":"Transition Metal Oxide Nanomaterials","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2507","display_name":"Polymers and Plastics"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cmos","display_name":"CMOS","score":0.7871285676956177},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7156689167022705},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6491143703460693},{"id":"https://openalex.org/keywords/memristor","display_name":"Memristor","score":0.6259602904319763},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.488753080368042},{"id":"https://openalex.org/keywords/adder","display_name":"Adder","score":0.4670238792896271},{"id":"https://openalex.org/keywords/multiplication","display_name":"Multiplication (music)","score":0.45422250032424927},{"id":"https://openalex.org/keywords/computational-science","display_name":"Computational science","score":0.4527478814125061},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.4516706168651581},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.44142821431159973},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.4336361885070801},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.415813148021698},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.39100098609924316},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3030513525009155},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2838643789291382},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1858125627040863},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18281546235084534},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.16109997034072876},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15172159671783447},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.14028677344322205}],"concepts":[{"id":"https://openalex.org/C46362747","wikidata":"https://www.wikidata.org/wiki/Q173431","display_name":"CMOS","level":2,"score":0.7871285676956177},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7156689167022705},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6491143703460693},{"id":"https://openalex.org/C150072547","wikidata":"https://www.wikidata.org/wiki/Q212923","display_name":"Memristor","level":2,"score":0.6259602904319763},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.488753080368042},{"id":"https://openalex.org/C164620267","wikidata":"https://www.wikidata.org/wiki/Q376953","display_name":"Adder","level":3,"score":0.4670238792896271},{"id":"https://openalex.org/C2780595030","wikidata":"https://www.wikidata.org/wiki/Q3860309","display_name":"Multiplication (music)","level":2,"score":0.45422250032424927},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.4527478814125061},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.4516706168651581},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.44142821431159973},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.4336361885070801},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.415813148021698},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.39100098609924316},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3030513525009155},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2838643789291382},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1858125627040863},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18281546235084534},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.16109997034072876},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15172159671783447},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14028677344322205},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2897937.2898042","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2897937.2898042","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/2897937.2898042","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 53rd Annual Design Automation Conference","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/2897937.2898042","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2897937.2898042","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/2897937.2898042","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 53rd Annual Design Automation Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.9100000262260437}],"awards":[{"id":"https://openalex.org/G3072929020","display_name":null,"funder_award_id":"C-SPIN","funder_id":"https://openalex.org/F4320306087","funder_display_name":"Semiconductor Research Corporation"},{"id":"https://openalex.org/G490593687","display_name":null,"funder_award_id":"Intel","funder_id":"https://openalex.org/F4320306087","funder_display_name":"Semiconductor Research Corporation"},{"id":"https://openalex.org/G6894402473","display_name":null,"funder_award_id":"Fellowship","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306087","display_name":"Semiconductor Research Corporation","ror":"https://ror.org/047z4n946"},{"id":"https://openalex.org/F4320307102","display_name":"Intel Corporation","ror":"https://ror.org/01ek73717"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2400523863.pdf","grobid_xml":"https://content.openalex.org/works/W2400523863.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1965304117","https://openalex.org/W1967111356","https://openalex.org/W1982240419","https://openalex.org/W1991813033","https://openalex.org/W1996092882","https://openalex.org/W2016922062","https://openalex.org/W2018459139","https://openalex.org/W2029479992","https://openalex.org/W2063219138","https://openalex.org/W2072790036","https://openalex.org/W2076358957","https://openalex.org/W2077586448","https://openalex.org/W2096199318","https://openalex.org/W2100115174","https://openalex.org/W2142805504","https://openalex.org/W2156728623","https://openalex.org/W2171394417","https://openalex.org/W2334364695","https://openalex.org/W2963050113"],"related_works":["https://openalex.org/W4229452466","https://openalex.org/W2966276069","https://openalex.org/W2304829496","https://openalex.org/W2358307108","https://openalex.org/W2017990332","https://openalex.org/W2080337923","https://openalex.org/W1488776355","https://openalex.org/W2093251826","https://openalex.org/W4221155546","https://openalex.org/W4244262766"],"abstract_inverted_index":{"Convolution":[0],"serves":[1],"as":[2],"the":[3,34,57,77],"basic":[4],"computational":[5],"primitive":[6],"for":[7,56,88],"various":[8],"associative":[9],"computing":[10,59],"tasks":[11],"ranging":[12],"from":[13],"edge":[14,89],"detection":[15,90],"to":[16,33,75,98],"image":[17],"matching.":[18],"CMOS":[19,71],"implementation":[20],"of":[21,37,63,85],"such":[22],"computations":[23],"entails":[24],"significant":[25],"bottlenecks":[26],"in":[27],"area":[28],"and":[29,39,51],"energy":[30,95],"consumption":[31,96],"due":[32],"large":[35],"number":[36],"multiplication":[38],"addition":[40],"operations":[41],"involved.":[42],"In":[43],"this":[44],"paper,":[45],"we":[46],"propose":[47],"an":[48],"ultra-low":[49],"power":[50],"compact":[52],"hybrid":[53],"spintronic-CMOS":[54],"design":[55],"convolution":[58,78],"unit.":[60],"Low-voltage":[61],"operation":[62,79],"domain-wall":[64],"motion":[65],"based":[66],"magneto-metallic":[67],"\"Spin-Memristor\"s":[68],"interfaced":[69],"with":[70,80],"circuits":[72],"is":[73],"able":[74],"perform":[76],"reasonable":[81],"accuracy.":[82],"Simulation":[83],"results":[84],"Gabor":[86],"filtering":[87],"reveal":[91],"~":[92],"2.5\u00d7":[93],"lower":[94],"compared":[97],"a":[99],"baseline":[100],"45nm-CMOS":[101],"implementation.":[102]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
