{"id":"https://openalex.org/W2805352912","doi":"https://doi.org/10.1145/3194554.3194578","title":"Towards Near-Data Processing of Compare Operations in 3D-Stacked Memory","display_name":"Towards Near-Data Processing of Compare Operations in 3D-Stacked Memory","publication_year":2018,"publication_date":"2018-05-30","ids":{"openalex":"https://openalex.org/W2805352912","doi":"https://doi.org/10.1145/3194554.3194578","mag":"2805352912"},"language":"en","primary_location":{"id":"doi:10.1145/3194554.3194578","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3194554.3194578","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Great Lakes Symposium on VLSI","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021176902","display_name":"Palash Das","orcid":"https://orcid.org/0000-0002-1979-0298"},"institutions":[{"id":"https://openalex.org/I1317621060","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079","country_code":"IN","type":"education","lineage":["https://openalex.org/I1317621060"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Palash Das","raw_affiliation_strings":["Indian Institute of Technology, Guwahati, Guwahati, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Guwahati, Guwahati, India","institution_ids":["https://openalex.org/I1317621060"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070605948","display_name":"Hemangee K. Kapoor","orcid":"https://orcid.org/0000-0002-9376-7686"},"institutions":[{"id":"https://openalex.org/I1317621060","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079","country_code":"IN","type":"education","lineage":["https://openalex.org/I1317621060"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Hemangee K. Kapoor","raw_affiliation_strings":["Indian Institute of Technology, Guwahati, Guwahati, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Guwahati, Guwahati, India","institution_ids":["https://openalex.org/I1317621060"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5021176902"],"corresponding_institution_ids":["https://openalex.org/I1317621060"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.05964312,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"243","last_page":"248"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11181","display_name":"Advanced Data Storage Technologies","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10829","display_name":"Interconnection Networks and Systems","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8514269590377808},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.664082407951355},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6106960773468018},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.504838764667511},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.43409228324890137},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.40605419874191284},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.3446786403656006}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8514269590377808},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.664082407951355},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6106960773468018},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.504838764667511},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.43409228324890137},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.40605419874191284},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3446786403656006},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3194554.3194578","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3194554.3194578","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Great Lakes Symposium on VLSI","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.9100000262260437}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W755906292","https://openalex.org/W1578512165","https://openalex.org/W1974607091","https://openalex.org/W1975237352","https://openalex.org/W1981220134","https://openalex.org/W1981943579","https://openalex.org/W2005112390","https://openalex.org/W2013435193","https://openalex.org/W2042747508","https://openalex.org/W2045431893","https://openalex.org/W2078141470","https://openalex.org/W2086112773","https://openalex.org/W2092324191","https://openalex.org/W2114440330","https://openalex.org/W2130517400","https://openalex.org/W2143909327","https://openalex.org/W2147657366","https://openalex.org/W2170382128","https://openalex.org/W2335240678","https://openalex.org/W2347068719","https://openalex.org/W2464177207","https://openalex.org/W2474451066","https://openalex.org/W2545376626","https://openalex.org/W2587913965"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1001352512","https://openalex.org/W1989889224","https://openalex.org/W4382618745","https://openalex.org/W1973775000","https://openalex.org/W2748922771","https://openalex.org/W1987128138"],"abstract_inverted_index":{"The":[0],"gap":[1],"between":[2],"the":[3,11,20,41,45,54,66,84,88,111,121,130,140,186,190],"processing":[4,49],"speed":[5,9],"and":[6,110,127,153,159,162,174,180],"memory":[7,90],"access":[8],"of":[10,37,47,57,68,87,142],"modern":[12],"multi-core":[13],"systems":[14],"has":[15,28],"become":[16,29],"a":[17,30,62,76],"bottleneck":[18],"for":[19],"emerging":[21],"data-intensive":[22],"workloads.":[23],"In":[24,184],"this":[25],"scenario,":[26],"it":[27],"smarter":[31],"idea":[32],"to":[33,40],"move":[34],"some":[35],"amount":[36],"computation":[38],"closer":[39],"data,":[42],"thus":[43],"stimulating":[44],"concept":[46],"near-data":[48,72],"(NDP).":[50],"Compare":[51],"or":[52],"scanning,":[53],"core":[55],"operations":[56,155],"many":[58],"applications,":[59],"typically":[60],"in":[61,178],"database,":[63],"can":[64,80],"leverage":[65],"benefits":[67],"NDP.":[69],"We":[70,170],"propose":[71],"compare":[73],"unit":[74],"(NDCU),":[75],"less-invasive":[77],"hardware,":[78],"that":[79],"be":[81],"integrated":[82],"with":[83,106,115,136],"existing":[85],"ecosystem":[86],"hybrid":[89],"cube":[91],"(HMC).":[92],"While":[93,120],"integrating":[94],"NDCU,":[95],"we":[96,147,188],"have":[97,148],"designed":[98],"two":[99],"full-system":[100],"architectures,":[101],"one":[102,132],"is":[103,113,124,133],"lighter":[104],"NDP":[105,114],"no":[107],"parallelism":[108,118],"(NNP)":[109],"second":[112,131],"vault":[116],"level":[117],"(NVLP).":[119],"first":[122],"architecture":[123],"more":[125],"power":[126],"area":[128],"efficient,":[129],"very":[134],"fast":[135],"negligible":[137],"overheads.":[138],"With":[139],"motive":[141],"carrying":[143],"out":[144],"scan":[145],"operation,":[146],"specifically":[149],"implemented":[150],"'compare-n-hit',":[151],"'compare-n-count'":[152],"'compare-n-max'":[154],"on":[156,196],"both":[157,185],"row-store":[158],"column-store":[160],"databases":[161],"found":[163],"significant":[164],"improvements":[165],"over":[166],"conventional":[167],"CPU-based":[168],"system.":[169],"get":[171],"around":[172,194],"2.3x":[173],"37x":[175],"performance":[176],"improvement":[177],"NNP":[179],"NVLP":[181],"architectures":[182],"respectively.":[183],"designs,":[187],"reduce":[189],"energy":[191],"consumption":[192],"by":[193],"8x":[195],"an":[197],"average.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}