{"id":"https://openalex.org/W7167015083","doi":"https://doi.org/10.1145/3797905.3807860","title":"HoloGraph: Bridging the Throughput Gap in Heterogeneous Graph Pattern Matching via Workload-Aware Steering","display_name":"HoloGraph: Bridging the Throughput Gap in Heterogeneous Graph Pattern Matching via Workload-Aware Steering","publication_year":2026,"publication_date":"2026-07-02","ids":{"openalex":"https://openalex.org/W7167015083","doi":"https://doi.org/10.1145/3797905.3807860"},"language":null,"primary_location":{"id":"doi:10.1145/3797905.3807860","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3797905.3807860","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th ACM International Conference on Supercomputing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3797905.3807860","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139890754","display_name":"Haotian Ma","orcid":"https://orcid.org/0009-0002-8767-2629"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haotian Ma","raw_affiliation_strings":["School of Data Science, The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0009-0002-8767-2629","affiliations":[{"raw_affiliation_string":"School of Data Science, The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017207899","display_name":"Wei\u2010Chung Hsu","orcid":"https://orcid.org/0000-0002-0833-7981"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei-Chung Hsu","raw_affiliation_strings":["School of Data Science, The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0002-0833-7981","affiliations":[{"raw_affiliation_string":"School of Data Science, The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043627040","display_name":"Yeh\u2010Ching Chung","orcid":"https://orcid.org/0000-0002-8704-9821"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yeh-Ching Chung","raw_affiliation_strings":["School of Data Science, The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0002-8704-9821","affiliations":[{"raw_affiliation_string":"School of Data Science, The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210116924"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"565","last_page":"575"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9803000092506409,"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":0.9803000092506409,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.002899999963119626,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.0026000000070780516,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5878000259399414},{"id":"https://openalex.org/keywords/pci-express","display_name":"PCI Express","score":0.5817999839782715},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5482000112533569},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.5325999855995178},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.5091000199317932},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4359000027179718},{"id":"https://openalex.org/keywords/interconnection","display_name":"Interconnection","score":0.41290000081062317},{"id":"https://openalex.org/keywords/power-consumption","display_name":"Power consumption","score":0.39640000462532043},{"id":"https://openalex.org/keywords/pattern-matching","display_name":"Pattern matching","score":0.387800008058548}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7735999822616577},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5878000259399414},{"id":"https://openalex.org/C64270927","wikidata":"https://www.wikidata.org/wiki/Q206924","display_name":"PCI Express","level":3,"score":0.5817999839782715},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5482000112533569},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.5325999855995178},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.5091000199317932},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.44339999556541443},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4359000027179718},{"id":"https://openalex.org/C123745756","wikidata":"https://www.wikidata.org/wiki/Q1665949","display_name":"Interconnection","level":2,"score":0.41290000081062317},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.39640000462532043},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3961000144481659},{"id":"https://openalex.org/C68859911","wikidata":"https://www.wikidata.org/wiki/Q1503724","display_name":"Pattern matching","level":2,"score":0.387800008058548},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3474999964237213},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3458000123500824},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C106891557","wikidata":"https://www.wikidata.org/wiki/Q4148051","display_name":"Wait-for graph","level":4,"score":0.3109000027179718},{"id":"https://openalex.org/C557945733","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Data transmission","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.29809999465942383},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.2962000072002411},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C115874739","wikidata":"https://www.wikidata.org/wiki/Q825377","display_name":"Critical path method","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.26969999074935913},{"id":"https://openalex.org/C2779172887","wikidata":"https://www.wikidata.org/wiki/Q184316","display_name":"PageRank","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3797905.3807860","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3797905.3807860","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th ACM International Conference on Supercomputing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3797905.3807860","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3797905.3807860","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th ACM International Conference on Supercomputing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1994727615","https://openalex.org/W2056524360","https://openalex.org/W2068015060","https://openalex.org/W2082773934","https://openalex.org/W2101196063","https://openalex.org/W2102039892","https://openalex.org/W2102931907","https://openalex.org/W2141629057","https://openalex.org/W2161723275","https://openalex.org/W2492149513","https://openalex.org/W2798875768","https://openalex.org/W2799267250","https://openalex.org/W2804502241","https://openalex.org/W2805710541","https://openalex.org/W2951870329","https://openalex.org/W2963066364","https://openalex.org/W2970204999","https://openalex.org/W2981963339","https://openalex.org/W3014850249","https://openalex.org/W3021196172","https://openalex.org/W3030126027","https://openalex.org/W3097653461","https://openalex.org/W3126138172","https://openalex.org/W3164237119","https://openalex.org/W3166986506","https://openalex.org/W3169645941","https://openalex.org/W3191648064","https://openalex.org/W3206583875","https://openalex.org/W4244579861","https://openalex.org/W4381328644","https://openalex.org/W4393183677","https://openalex.org/W4411403454"],"related_works":[],"abstract_inverted_index":{"Graph":[0],"Pattern":[1],"Matching":[2],"(GPM)":[3],"is":[4],"a":[5,23],"computationally":[6],"demanding":[7],"workload":[8],"essential":[9],"for":[10],"modern":[11],"data":[12,70],"analytics.":[13],"While":[14],"emerging":[15],"systems":[16,28,48],"offer":[17,49],"massive":[18,50],"performance,":[19],"they":[20],"suffer":[21],"from":[22],"fundamental":[24],"throughput":[25,40,72],"mismatch.":[26],"CPU-centric":[27],"leverage":[29],"large":[30],"host":[31],"memory":[32],"but":[33,53],"are":[34,54],"constrained":[35],"by":[36,57],"limited":[37],"arithmetic":[38],"instruction":[39],"during":[41],"intensive":[42],"set":[43],"intersection":[44],"operations.":[45],"Conversely,":[46],"GPU-accelerated":[47],"compute":[51,81],"power":[52],"strictly":[55],"bound":[56],"PCIe":[58],"interconnect":[59],"bandwidth.":[60],"When":[61],"processing":[62],"large-scale":[63],"graphs":[64],"that":[65],"exceed":[66],"device":[67],"memory,":[68],"the":[69,76],"transfer":[71],"lags":[73],"significantly":[74],"behind":[75],"device\u2019s":[77],"consumption":[78],"rate,":[79],"leaving":[80],"engines":[82],"starved.":[83]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-07-03T00:00:00"}
