{"id":"https://openalex.org/W4409138483","doi":"https://doi.org/10.1587/transinf.2024edp7319","title":"Performance and Power-Efficiency Improvements on Graph Embedding using Sequential Training Algorithm and FPGA","display_name":"Performance and Power-Efficiency Improvements on Graph Embedding using Sequential Training Algorithm and FPGA","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409138483","doi":"https://doi.org/10.1587/transinf.2024edp7319"},"language":"en","primary_location":{"id":"doi:10.1587/transinf.2024edp7319","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2024edp7319","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/advpub/0/advpub_2024EDP7319/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.jstage.jst.go.jp/article/transinf/advpub/0/advpub_2024EDP7319/_pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027081053","display_name":"Kazuki Sunaga","orcid":"https://orcid.org/0009-0007-0893-8115"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuki SUNAGA","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034929598","display_name":"Keisuke Sugiura","orcid":"https://orcid.org/0000-0002-3839-1815"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keisuke SUGIURA","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041549339","display_name":"Hiroki Matsutani","orcid":"https://orcid.org/0000-0001-9578-3842"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroki MATSUTANI","raw_affiliation_strings":["Graduate School of Science and Technology, Keio University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Technology, Keio University","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02078913,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.8819000124931335,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.8819000124931335,"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.8671000003814697,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.8264999985694885,"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":0.8766602873802185},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.6347471475601196},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5845257043838501},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47235095500946045},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4502899944782257},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.42033326625823975},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41146230697631836},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2930278182029724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2629033923149109},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.22378847002983093}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8766602873802185},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.6347471475601196},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5845257043838501},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47235095500946045},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4502899944782257},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.42033326625823975},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41146230697631836},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2930278182029724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2629033923149109},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.22378847002983093},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1587/transinf.2024edp7319","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2024edp7319","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/advpub/0/advpub_2024EDP7319/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1587/transinf.2024edp7319","is_oa":true,"landing_page_url":"https://doi.org/10.1587/transinf.2024edp7319","pdf_url":"https://www.jstage.jst.go.jp/article/transinf/advpub/0/advpub_2024EDP7319/_pdf","source":{"id":"https://openalex.org/S2486202937","display_name":"IEICE Transactions on Information and Systems","issn_l":"0916-8532","issn":["0916-8532","1745-1361"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4320800604","host_organization_name":"Institute of Electronics, Information and Communication Engineers","host_organization_lineage":["https://openalex.org/P4320800604"],"host_organization_lineage_names":["Institute of Electronics, Information and Communication Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEICE Transactions on Information and Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8299999833106995,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G2905652878","display_name":"\u5c0f\u578b\u79fb\u52d5\u30ed\u30dc\u30c3\u30c8\u5411\u3051\u6df1\u5c64\u5b66\u7fd2\u30d9\u30fc\u30b9SLAM\u6280\u8853\u306e\u958b\u767a\u3068\u305d\u306e\u30cf\u30fc\u30c9\u30a6\u30a7\u30a2\u5316","funder_award_id":"22KJ2716","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4409138483.pdf","grobid_xml":"https://content.openalex.org/works/W4409138483.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2081900870","https://openalex.org/W2111241003","https://openalex.org/W2233261550","https://openalex.org/W2355315220","https://openalex.org/W4200391368","https://openalex.org/W2210979487","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352"],"abstract_inverted_index":{"Recently,":[0],"graph":[1,23,30,56,65,108,119,222,232],"structures":[2,120],"have":[3,89],"been":[4],"utilized":[5],"in":[6,127,190,211,243],"IoT":[7,123],"(Internet":[8],"of":[9,28,42,48,118,135,186,245],"Things)":[10],"environments":[11],"such":[12,54],"as":[13,31],"network":[14],"anomaly":[15],"detection,":[16],"smart":[17,20],"transportation,":[18],"and":[19,141,249,264],"grids.":[21],"A":[22],"embedding":[24,57,223],"is":[25,46,146,241],"a":[26,29,32,55,63,67,78,133,166,226],"representation":[27],"fixed-length,":[33],"low-dimensional":[34],"vector,":[35],"which":[36,99],"can":[37,219],"concisely":[38],"represent":[39],"the":[40,43,49,72,92,97,107,112,116,122,173,184,187,191,208,212,215,231,237,246,250,257,262],"characteristics":[41],"graph.":[44],"node2vec":[45,74],"one":[47],"well-known":[50],"algorithms":[51],"for":[52,103,155],"obtaining":[53],"by":[58],"sampling":[59],"neighboring":[60],"nodes":[61],"on":[62,77,148,176,202],"given":[64],"using":[66,82],"random":[68],"walk":[69],"technique.":[70],"However,":[71],"original":[73,174,213],"algorithm":[75,140],"relies":[76],"conventional":[79],"batch":[80],"training":[81,93,139,193],"backpropagation":[83],"algorithm.":[84],"In":[85,235],"other":[86],"words,":[87],"we":[88],"to":[90,95,165,172,261],"retain":[91],"data":[94],"retrain":[96],"model,":[98,214],"makes":[100],"it":[101,254],"unsuitable":[102],"real-world":[104],"applications":[105],"where":[106],"structure":[109,233],"changes":[110,117],"after":[111,121],"deployment.":[113],"To":[114],"address":[115],"devices":[124],"are":[125],"deployed":[126],"edge":[128],"environments,":[129],"this":[130],"paper":[131],"proposes":[132],"combination":[134],"an":[136,149,177],"online":[137],"sequential":[138,157,192,217],"node2vec.":[142],"The":[143,159],"proposed":[144,160,188,216,238],"model":[145,175,189,218],"implemented":[147],"FPGA":[150,161,239],"(Field-Programmable":[151],"Gate":[152],"Array)":[153],"device":[154],"efficient":[156],"training.":[158],"implementation":[162,240],"achieves":[163,225],"up":[164],"205.25":[167],"times":[168],"speed":[169],"improvement":[170],"compared":[171,260],"ARM":[178],"Cortex-A53":[179],"CPU.":[180],"We":[181],"also":[182],"evaluate":[183],"performance":[185],"task":[194],"from":[195],"various":[196],"perspectives.":[197],"For":[198],"example,":[199],"evaluation":[200],"results":[201,251],"dynamic":[203],"graphs":[204],"show":[205,252],"that":[206,224,253],"while":[207],"accuracy":[209,228],"decreases":[210],"obtain":[220],"better":[221],"higher":[227],"even":[229],"when":[230],"changes.":[234],"addition,":[236],"evaluated":[242],"terms":[244],"power":[247,258],"consumption,":[248],"significantly":[255],"improves":[256],"efficiency":[259],"CPU":[263],"embedded":[265],"GPU":[266],"implementations.":[267]},"counts_by_year":[],"updated_date":"2026-08-23T07:36:19.812096","created_date":"2025-10-10T00:00:00"}
