{"id":"https://openalex.org/W7163409775","doi":"https://doi.org/10.48550/arxiv.2606.02836","title":"Fast Transformer Inference on ARM-Based HMPSoCs","display_name":"Fast Transformer Inference on ARM-Based HMPSoCs","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7163409775","doi":"https://doi.org/10.48550/arxiv.2606.02836"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.02836","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02836","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.02836","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137766255","display_name":"Hang Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Hang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021445324","display_name":"Yixian Shen","orcid":"https://orcid.org/0000-0001-8447-872X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Yixian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070813911","display_name":"Thanassis Giannetsos","orcid":"https://orcid.org/0000-0003-0663-2263"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Giannetsos, Thanassis","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067055700","display_name":"Anuj Pathania","orcid":"https://orcid.org/0000-0002-5813-7021"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pathania, Anuj","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.7371000051498413,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.7371000051498413,"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":0.050200000405311584,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.03830000013113022,"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/inference","display_name":"Inference","score":0.767300009727478},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6761000156402588},{"id":"https://openalex.org/keywords/inference-engine","display_name":"Inference engine","score":0.42100000381469727},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.3603000044822693},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.3564999997615814},{"id":"https://openalex.org/keywords/flyback-transformer","display_name":"Flyback transformer","score":0.33320000767707825}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.767300009727478},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6761000156402588},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.609000027179718},{"id":"https://openalex.org/C46743427","wikidata":"https://www.wikidata.org/wiki/Q1341685","display_name":"Inference engine","level":3,"score":0.42100000381469727},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.3603000044822693},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.3564999997615814},{"id":"https://openalex.org/C17321440","wikidata":"https://www.wikidata.org/wiki/Q184909","display_name":"Flyback transformer","level":4,"score":0.33320000767707825},{"id":"https://openalex.org/C117323899","wikidata":"https://www.wikidata.org/wiki/Q1907989","display_name":"Distribution transformer","level":4,"score":0.33180001378059387},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2939000129699707},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.29109999537467957},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.27250000834465027},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.267300009727478},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.25949999690055847},{"id":"https://openalex.org/C49154492","wikidata":"https://www.wikidata.org/wiki/Q5300","display_name":"Central processing unit","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.02836","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02836","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.02836","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.02836","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Transformer":[0],"models":[1],"have":[2],"set":[3],"new":[4,53],"performance":[5],"standards":[6],"for":[7,20,44,115],"machine":[8],"learning":[9],"(ML)":[10],"tasks.":[11],"However,":[12],"their":[13],"resource-intensive":[14],"deployment":[15],"on":[16,37,79,108,142],"resource-constrained":[17],"edge":[18,39,90],"devices":[19,40,91],"cloud-free,":[21],"on-chip":[22],"transformer":[23,45,54,61,72,102,129],"inference":[24,36,73,130,141],"remains":[25],"challenging.":[26],"The":[27],"ARM":[28],"Compute":[29],"Library":[30],"(ARM-CL)":[31],"framework":[32],"provides":[33],"low-latency":[34],"CNN":[35],"ARM-based":[38,81],"but":[41],"lacks":[42],"support":[43,59],"inference.":[46],"In":[47],"this":[48],"work,":[49],"we":[50],"implement":[51],"several":[52],"kernels":[55],"in":[56],"ARM-CL":[57,65],"to":[58,68,75,134,137],"native":[60],"execution.":[62],"Our":[63],"extended":[64],"achieves":[66],"up":[67,133],"three":[69],"times":[70],"faster":[71],"compared":[74,136],"state-of-the-art":[76],"CPU/GPU":[77],"implementations":[78],"an":[80],"embedded":[82,94],"board.":[83],"Furthermore,":[84],"heterogeneous":[85],"multi-processor":[86],"system-on-chips":[87],"(HMPSoCs)":[88],"powering":[89],"provide":[92],"both":[93],"CPUs":[95],"and":[96],"GPUs.":[97],"We":[98],"introduce":[99],"cooperative":[100,121],"CPU-GPU":[101],"inference,":[103],"which":[104],"executes":[105],"memory-intensive":[106],"operations":[107],"the":[109,113,138],"CPU":[110],"while":[111],"utilizing":[112],"GPU":[114],"highly":[116],"parallelizable,":[117],"compute-intensive":[118],"operations.":[119],"This":[120],"execution,":[122],"implemented":[123],"with":[124],"minimal":[125],"overhead,":[126],"further":[127],"reduces":[128],"latency":[131],"by":[132],"15.72%":[135],"best":[139],"single-processor":[140],"ARM-CL.":[143]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-04T00:00:00"}