{"id":"https://openalex.org/W2946571646","doi":"https://doi.org/10.1145/3299874.3317984","title":"GraphiDe","display_name":"GraphiDe","publication_year":2019,"publication_date":"2019-05-13","ids":{"openalex":"https://openalex.org/W2946571646","doi":"https://doi.org/10.1145/3299874.3317984","mag":"2946571646"},"language":"en","primary_location":{"id":"doi:10.1145/3299874.3317984","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3299874.3317984","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3299874.3317984","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 Great Lakes Symposium on VLSI","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3299874.3317984","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051680668","display_name":"Shaahin Angizi","orcid":"https://orcid.org/0000-0003-2289-6381"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaahin Angizi","raw_affiliation_strings":["University of Central Florida, Orlando, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047916979","display_name":"Deliang Fan","orcid":"https://orcid.org/0000-0002-7989-6297"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deliang Fan","raw_affiliation_strings":["University of Central Florida, Orlando, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I106165777"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":51,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"45","last_page":"50"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":0.9983000159263611,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9977999925613403,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9975000023841858,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.817840576171875},{"id":"https://openalex.org/keywords/dram","display_name":"Dram","score":0.8008649349212646},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.607210636138916},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5663094520568848},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5634626150131226},{"id":"https://openalex.org/keywords/cas-latency","display_name":"CAS latency","score":0.5012085437774658},{"id":"https://openalex.org/keywords/massively-parallel","display_name":"Massively parallel","score":0.42435142397880554},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.41729307174682617},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.3561726212501526},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.30469247698783875},{"id":"https://openalex.org/keywords/memory-controller","display_name":"Memory controller","score":0.14228102564811707}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.817840576171875},{"id":"https://openalex.org/C7366592","wikidata":"https://www.wikidata.org/wiki/Q1255620","display_name":"Dram","level":2,"score":0.8008649349212646},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.607210636138916},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5663094520568848},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5634626150131226},{"id":"https://openalex.org/C189930140","wikidata":"https://www.wikidata.org/wiki/Q1112878","display_name":"CAS latency","level":4,"score":0.5012085437774658},{"id":"https://openalex.org/C190475519","wikidata":"https://www.wikidata.org/wiki/Q544384","display_name":"Massively parallel","level":2,"score":0.42435142397880554},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.41729307174682617},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3561726212501526},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.30469247698783875},{"id":"https://openalex.org/C100800780","wikidata":"https://www.wikidata.org/wiki/Q1175867","display_name":"Memory controller","level":3,"score":0.14228102564811707},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C98986596","wikidata":"https://www.wikidata.org/wiki/Q1143031","display_name":"Semiconductor memory","level":2,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3299874.3317984","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3299874.3317984","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3299874.3317984","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 Great Lakes Symposium on VLSI","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3299874.3317984","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3299874.3317984","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3299874.3317984","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 Great Lakes Symposium on VLSI","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G1261258159","display_name":"E2CDA: Type II: Non-Volatile In-Memory Processing Unit: Memory, In-Memory Logic and Deep Neural Network","funder_award_id":"1740126","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G500980815","display_name":null,"funder_award_id":"1740126","funder_id":"https://openalex.org/F4320306087","funder_display_name":"Semiconductor Research Corporation"}],"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"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2946571646.pdf","grobid_xml":"https://content.openalex.org/works/W2946571646.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W755906292","https://openalex.org/W1981943579","https://openalex.org/W2108880814","https://openalex.org/W2155461593","https://openalex.org/W2170257519","https://openalex.org/W2238633138","https://openalex.org/W2396622873","https://openalex.org/W2612654866","https://openalex.org/W2613569094","https://openalex.org/W2765234579","https://openalex.org/W2766489088","https://openalex.org/W2768145587","https://openalex.org/W2794532328","https://openalex.org/W2801000640","https://openalex.org/W2809205380","https://openalex.org/W2809295488","https://openalex.org/W2962903741"],"related_works":["https://openalex.org/W4293430534","https://openalex.org/W2342813629","https://openalex.org/W3150934690","https://openalex.org/W2335743642","https://openalex.org/W4297812927","https://openalex.org/W2800412005","https://openalex.org/W1976244802","https://openalex.org/W2083934844","https://openalex.org/W1992487929","https://openalex.org/W4386903460"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"GraphiDe,":[5],"a":[6],"novel":[7],"DRAM-based":[8],"processing-in-memory":[9],"(PIM)":[10],"accelerator":[11],"for":[12],"graph":[13,38],"processing.":[14],"It":[15,91],"transforms":[16],"current":[17],"DRAM":[18,87],"architecture":[19],"to":[20,35,45],"massively":[21],"parallel":[22],"computational":[23],"units":[24],"exploiting":[25],"the":[26,31,85],"high":[27],"internal":[28],"bandwidth":[29],"of":[30],"modern":[32],"memory":[33],"chips":[34],"accelerate":[36],"various":[37],"processing":[39],"applications.":[40],"GraphiDe":[41,74],"can":[42],"be":[43],"leveraged":[44],"greatly":[46],"reduce":[47],"energy":[48],"consumption":[49],"and":[50,81,96],"latency":[51],"dealing":[52],"with":[53],"underlying":[54],"adjacency":[55],"matrix":[56],"computations":[57],"by":[58],"eliminating":[59],"unnecessary":[60],"off-chip":[61],"accesses.":[62],"The":[63],"extensive":[64],"circuit-architecture":[65],"simulations":[66],"over":[67,84,99],"three":[68],"social":[69],"network":[70],"data-sets":[71],"indicate":[72],"that":[73],"achieves":[75,92],"on":[76],"average":[77],"3.1x":[78],"energy-efficiency":[79,95],"improvement":[80],"4.2x":[82],"speed-up":[83,98],"recent":[86],"based":[88],"PIM":[89],"platform.":[90],"~59x":[93],"higher":[94],"83x":[97],"GPU-based":[100],"acceleration":[101],"methods.":[102]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2019-05-29T00:00:00"}
