{"id":"https://openalex.org/W4411358985","doi":"https://doi.org/10.1109/lca.2025.3580562","title":"Stardust: Scalable and Transferable Workload Mapping for Large AI on Multi-Chiplet Systems","display_name":"Stardust: Scalable and Transferable Workload Mapping for Large AI on Multi-Chiplet Systems","publication_year":2025,"publication_date":"2025-06-17","ids":{"openalex":"https://openalex.org/W4411358985","doi":"https://doi.org/10.1109/lca.2025.3580562"},"language":"en","primary_location":{"id":"doi:10.1109/lca.2025.3580562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lca.2025.3580562","pdf_url":null,"source":{"id":"https://openalex.org/S17643076","display_name":"IEEE Computer Architecture Letters","issn_l":"1556-6056","issn":["1556-6056","1556-6064","2473-2575"],"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 Computer Architecture Letters","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/A5028417807","display_name":"Wencheng Zou","orcid":"https://orcid.org/0000-0001-8324-2600"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wencheng Zou","raw_affiliation_strings":["Department of Electrical and Computer Engineering, George Washington University, Washington, DC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, George Washington University, Washington, DC, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Feiyun Zhao","orcid":"https://orcid.org/0009-0004-0525-8817"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feiyun Zhao","raw_affiliation_strings":["Department of Electrical and Computer Engineering, George Washington University, Washington, DC, USA"],"raw_orcid":"https://orcid.org/0009-0004-0525-8817","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, George Washington University, Washington, DC, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065262986","display_name":"Nan Wu","orcid":"https://orcid.org/0000-0001-8291-4292"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nan Wu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, George Washington University, Washington, DC, USA"],"raw_orcid":"https://orcid.org/0000-0001-8291-4292","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, George Washington University, Washington, DC, USA","institution_ids":["https://openalex.org/I193531525"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I193531525"],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.2866,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.4986968,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"24","issue":"2","first_page":"201","last_page":"204"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9993000030517578,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.998199999332428,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9973000288009644,"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":0.8449167013168335},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.7386541366577148},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7295551300048828},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.4762401878833771},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3829262852668762},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1669553518295288},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.14291316270828247}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8449167013168335},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.7386541366577148},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7295551300048828},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.4762401878833771},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3829262852668762},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1669553518295288},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.14291316270828247}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lca.2025.3580562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lca.2025.3580562","pdf_url":null,"source":{"id":"https://openalex.org/S17643076","display_name":"IEEE Computer Architecture Letters","issn_l":"1556-6056","issn":["1556-6056","1556-6064","2473-2575"],"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 Computer Architecture Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3243164565","display_name":null,"funder_award_id":"2024-PK-3266-G","funder_id":"https://openalex.org/F4320306087","funder_display_name":"Semiconductor Research Corporation"}],"funders":[{"id":"https://openalex.org/F4320306087","display_name":"Semiconductor Research Corporation","ror":"https://ror.org/047z4n946"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1975442866","https://openalex.org/W2151936673","https://openalex.org/W2194775991","https://openalex.org/W2736601468","https://openalex.org/W2791175999","https://openalex.org/W2913104037","https://openalex.org/W2964391226","https://openalex.org/W2965373594","https://openalex.org/W2978633783","https://openalex.org/W2980104813","https://openalex.org/W3016874508","https://openalex.org/W3094031577","https://openalex.org/W3122890974","https://openalex.org/W3138516171","https://openalex.org/W3192336523","https://openalex.org/W3212496002","https://openalex.org/W3215626407","https://openalex.org/W4287749054","https://openalex.org/W4288089799","https://openalex.org/W4311263198","https://openalex.org/W4384918448","https://openalex.org/W4390872447","https://openalex.org/W4393592481","https://openalex.org/W6738144653","https://openalex.org/W6738964360","https://openalex.org/W6741002519","https://openalex.org/W6748687944","https://openalex.org/W6751627690","https://openalex.org/W6755164397","https://openalex.org/W6766673545","https://openalex.org/W6768695126","https://openalex.org/W6769627184","https://openalex.org/W6779068807","https://openalex.org/W6780230476","https://openalex.org/W6784370339","https://openalex.org/W6790978476","https://openalex.org/W6791353385","https://openalex.org/W6796931752","https://openalex.org/W6803872405","https://openalex.org/W6803958908","https://openalex.org/W6811145144","https://openalex.org/W6839075354","https://openalex.org/W6851592950","https://openalex.org/W6852874933","https://openalex.org/W6854866820","https://openalex.org/W6858023062"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W1982914007","https://openalex.org/W2159583675","https://openalex.org/W1824242903","https://openalex.org/W1493858311","https://openalex.org/W2155470929","https://openalex.org/W2111125783","https://openalex.org/W2394465510"],"abstract_inverted_index":{"Workload":[0],"partitioning":[1],"and":[2,22,56,81],"mapping":[3],"are":[4],"critical":[5],"to":[6,43,52,91,94],"optimizing":[7],"performance":[8],"in":[9,18,79],"multi-chiplet":[10,38],"systems.":[11],"However,":[12],"existing":[13],"approaches":[14],"struggle":[15],"with":[16],"scalability":[17],"large":[19],"search":[20],"spaces":[21],"lack":[23],"transferability":[24],"across":[25],"different":[26],"workloads.":[27],"To":[28],"overcome":[29],"these":[30],"limitations,":[31],"we":[32],"proposeStardust,":[33],"ascalable":[34],"andtransferable":[35],"workloadmapping":[36],"on":[37,66],"systems.Stardustcombines":[39],"learnable":[40],"graph":[41],"clustering":[42],"downscale":[44],"computation":[45],"graphs":[46],"for":[47,61],"efficient":[48],"partitioning,":[49],"topology-masked":[50],"attention":[51],"capture":[53],"structural":[54],"information,":[55],"deep":[57],"reinforcement":[58],"learning":[59],"(DRL)":[60],"optimized":[62],"workload":[63],"mapping.":[64],"Evaluations":[65],"production-scale":[67],"AI":[68],"models":[69],"show":[70],"that":[71],"(1)Stardust-generated":[72],"mappings":[73],"significantly":[74],"outperform":[75],"commonly":[76],"used":[77],"heuristics":[78],"throughput,":[80],"(2)":[82],"fine-tuning":[83],"a":[84],"pre-trainedStardustmodel":[85],"improves":[86],"sample":[87],"efficiency":[88],"by":[89],"up":[90],"15\u00d7":[92],"compared":[93],"training":[95],"from":[96],"scratch.":[97]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-06-18T00:00:00"}
