{"id":"https://openalex.org/W2910317275","doi":"https://doi.org/10.1109/tc.2019.2893384","title":"HyVE: Hybrid Vertex-Edge Memory Hierarchy for Energy-Efficient Graph Processing","display_name":"HyVE: Hybrid Vertex-Edge Memory Hierarchy for Energy-Efficient Graph Processing","publication_year":2019,"publication_date":"2019-01-16","ids":{"openalex":"https://openalex.org/W2910317275","doi":"https://doi.org/10.1109/tc.2019.2893384","mag":"2910317275"},"language":"en","primary_location":{"id":"doi:10.1109/tc.2019.2893384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tc.2019.2893384","pdf_url":null,"source":{"id":"https://openalex.org/S157670870","display_name":"IEEE Transactions on Computers","issn_l":"0018-9340","issn":["0018-9340","1557-9956","2326-3814"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computers","raw_type":"journal-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/A5102805465","display_name":"Guohao Dai","orcid":"https://orcid.org/0000-0002-8464-0130"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guohao Dai","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049355973","display_name":"Tianhao Huang","orcid":"https://orcid.org/0009-0002-5384-2773"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianhao Huang","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100445061","display_name":"Yu Wang","orcid":"https://orcid.org/0000-0001-6108-5157"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Wang","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023755254","display_name":"Huazhong Yang","orcid":"https://orcid.org/0000-0003-2421-353X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huazhong Yang","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044520704","display_name":"John Wawrzynek","orcid":"https://orcid.org/0009-0003-1466-4553"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Wawrzynek","raw_affiliation_strings":["Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102805465"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.6131,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.71318381,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"68","issue":"8","first_page":"1131","last_page":"1146"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9905999898910522,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6193192601203918},{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.5454450845718384},{"id":"https://openalex.org/keywords/memory-hierarchy","display_name":"Memory hierarchy","score":0.48809942603111267},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4298645257949829},{"id":"https://openalex.org/keywords/out-of-core-algorithm","display_name":"Out-of-core algorithm","score":0.4287334084510803},{"id":"https://openalex.org/keywords/windmill-graph","display_name":"Windmill graph","score":0.4238194227218628},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.40737876296043396},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3304901719093323},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.22431305050849915},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.17814013361930847}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6193192601203918},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.5454450845718384},{"id":"https://openalex.org/C2778100165","wikidata":"https://www.wikidata.org/wiki/Q1589327","display_name":"Memory hierarchy","level":3,"score":0.48809942603111267},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4298645257949829},{"id":"https://openalex.org/C79470037","wikidata":"https://www.wikidata.org/wiki/Q279748","display_name":"Out-of-core algorithm","level":2,"score":0.4287334084510803},{"id":"https://openalex.org/C73380178","wikidata":"https://www.wikidata.org/wiki/Q8024306","display_name":"Windmill graph","level":5,"score":0.4238194227218628},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.40737876296043396},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3304901719093323},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.22431305050849915},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.17814013361930847},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tc.2019.2893384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tc.2019.2893384","pdf_url":null,"source":{"id":"https://openalex.org/S157670870","display_name":"IEEE Transactions on Computers","issn_l":"0018-9340","issn":["0018-9340","1557-9956","2326-3814"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G1799421016","display_name":null,"funder_award_id":"61832007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4403844069","display_name":null,"funder_award_id":"61621091","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6335303887","display_name":null,"funder_award_id":"61373026","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G738548397","display_name":null,"funder_award_id":"2017YFA0207600","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G7658708249","display_name":null,"funder_award_id":"61622403","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320309411","display_name":"University of California Berkeley","ror":"https://ror.org/01an7q238"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W78077100","https://openalex.org/W1448681276","https://openalex.org/W1788180225","https://openalex.org/W1832683484","https://openalex.org/W1854214752","https://openalex.org/W1966939297","https://openalex.org/W1969970763","https://openalex.org/W1981943579","https://openalex.org/W1987634495","https://openalex.org/W2010202670","https://openalex.org/W2013028205","https://openalex.org/W2018774711","https://openalex.org/W2020740707","https://openalex.org/W2034102265","https://openalex.org/W2053076698","https://openalex.org/W2055497547","https://openalex.org/W2096544401","https://openalex.org/W2168972302","https://openalex.org/W2170616854","https://openalex.org/W2282294254","https://openalex.org/W2284169075","https://openalex.org/W2508029414","https://openalex.org/W2515673159","https://openalex.org/W2524623326","https://openalex.org/W2545376626","https://openalex.org/W2566870951","https://openalex.org/W2584785188","https://openalex.org/W2621373082","https://openalex.org/W2792682036","https://openalex.org/W2794532328","https://openalex.org/W2795118915","https://openalex.org/W2899106831","https://openalex.org/W2950542868","https://openalex.org/W2962903741","https://openalex.org/W2963674932","https://openalex.org/W3099590572","https://openalex.org/W4234988573","https://openalex.org/W4241140669","https://openalex.org/W4252563462","https://openalex.org/W6603201521","https://openalex.org/W6628546715","https://openalex.org/W6638233953","https://openalex.org/W6638659379","https://openalex.org/W6639055396","https://openalex.org/W6684474170","https://openalex.org/W6727469013","https://openalex.org/W6738901727","https://openalex.org/W6756007819"],"related_works":["https://openalex.org/W108401543","https://openalex.org/W1944865817","https://openalex.org/W2279642117","https://openalex.org/W4300190729","https://openalex.org/W2953056293","https://openalex.org/W2560781234","https://openalex.org/W4200143910","https://openalex.org/W2081192312","https://openalex.org/W2019374455","https://openalex.org/W2489934651"],"abstract_inverted_index":{"High":[0],"energy":[1,17,91,114,171,189],"consumption":[2,92],"of":[3,13,38,51,153,167],"conventional":[4,98,179],"memory":[5,23,33,69,90,99,180],"modules":[6],"(e.g.,":[7,140],"DRAMs)":[8],"hinders":[9],"the":[10,36,113,122,161,176,193],"further":[11],"improvement":[12,173],"large-scale":[14],"graph":[15,58,73,123,138,196],"processing's":[16],"efficiency.":[18],"The":[19],"emerging":[20],"resistive":[21],"random-access":[22],"(ReRAM)":[24],"has":[25],"shown":[26],"great":[27],"potential":[28],"in":[29,57,137],"providing":[30],"an":[31],"energy-efficient":[32,72],"module.":[34],"However,":[35],"performance":[37],"ReRAMs":[39,131],"suffers":[40],"from":[41],"data":[42,82,105],"access":[43,80],"patterns":[44],"with":[45,97,175,192],"poor":[46],"locality":[47],"and":[48,81,107,118,169,178],"large":[49],"amounts":[50],"written":[52,83],"data,":[53],"which":[54,111],"are":[55,132,146],"common":[56],"processing.":[59,74],"In":[60,75],"this":[61],"paper,":[62],"we":[63,77,128],"propose":[64],"HyVE,":[65,76],"a":[66],"Hybrid":[67],"Vertex-Edge":[68],"hierarchy":[70,181],"for":[71,134,149],"avoid":[78],"random":[79],"to":[84],"ReRAM":[85,144],"modules.":[86],"HyVE":[87,186],"can":[88],"reduce":[89],"by":[93,116],"86.17":[94],"percent":[95],"compared":[96,174,191],"systems.":[100],"We":[101],"have":[102],"also":[103],"proposed":[104],"sharing":[106],"bank-level":[108],"power-gating":[109],"schemes,":[110],"improve":[112],"efficiency":[115,172],"1.60x":[117],"1.53x.":[119],"By":[120],"analyzing":[121],"processing":[124,139,150,197],"model":[125],"on":[126],"ReRAMs,":[127],"show":[129,159],"that":[130,160],"good":[133],"read-intensive":[135],"operations":[136],"reading":[141],"edges),":[142],"while":[143],"crossbars":[145],"not":[147],"suitable":[148],"edges":[151],"because":[152],"heavy":[154],"writing":[155],"overheads.":[156],"Our":[157],"evaluations":[158],"optimized":[162],"design":[163],"achieves":[164,187],"two":[165],"orders":[166],"magnitude":[168],"5.90x":[170],"CPU-based":[177],"based":[182],"designs,":[183],"respectively.":[184],"Moreover,":[185],"2.83x":[188],"reduction":[190],"previous":[194],"ReRAM-based":[195],"architecture.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}