{"id":"https://openalex.org/W7168290336","doi":"https://doi.org/10.48550/arxiv.2607.11211","title":"FastTPS: An Optimized Method for LLM Token Phase for AI accelerators","display_name":"FastTPS: An Optimized Method for LLM Token Phase for AI accelerators","publication_year":2026,"publication_date":"2026-07-13","ids":{"openalex":"https://openalex.org/W7168290336","doi":"https://doi.org/10.48550/arxiv.2607.11211"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.11211","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.11211","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":null,"license_id":null,"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.2607.11211","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5140719146","display_name":"Wenzong Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Wenzong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140723823","display_name":"Danyang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Danyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140671889","display_name":"Kun Cao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cao, Kun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140574223","display_name":"Tejus Siddagangaiah","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siddagangaiah, Tejus","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140600389","display_name":"Rajeev Patwari","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Patwari, Rajeev","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140736878","display_name":"Zhanxing Pu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pu, Zhanxing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140727032","display_name":"Siyin Kong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kong, Siyin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140699703","display_name":"Zijiang Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Zijiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140641446","display_name":"Hao Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140727745","display_name":"Varun Sharma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sharma, Varun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140582343","display_name":"Yue Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Yue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140698150","display_name":"Tianping Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Tianping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140734537","display_name":"Fan Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Fan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140737509","display_name":"Jicheng Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jicheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140653933","display_name":"Yushan Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yushan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140729584","display_name":"Fennian Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Fennian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140732456","display_name":"Aaron Ng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ng, Aaron","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140674338","display_name":"Elliott Delaye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Delaye, Elliott","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140661970","display_name":"Ashish Sirasao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sirasao, Ashish","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5140732652","display_name":"Sudip Nag","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nag, Sudip","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":0.13609999418258667,"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":0.13609999418258667,"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/T10028","display_name":"Topic Modeling","score":0.11840000003576279,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.11320000141859055,"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/security-token","display_name":"Security token","score":0.6050000190734863},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5199999809265137},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4449999928474426},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.43639999628067017},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.428600013256073},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.414000004529953},{"id":"https://openalex.org/keywords/high-memory","display_name":"High memory","score":0.3677999973297119},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3490000069141388}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8519999980926514},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.6050000190734863},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5199999809265137},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4528999924659729},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4449999928474426},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.43639999628067017},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.428600013256073},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.414000004529953},{"id":"https://openalex.org/C2781357197","wikidata":"https://www.wikidata.org/wiki/Q5757597","display_name":"High memory","level":2,"score":0.3677999973297119},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.33809998631477356},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.32280001044273376},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3165999948978424},{"id":"https://openalex.org/C157170001","wikidata":"https://www.wikidata.org/wiki/Q4781507","display_name":"Applications of artificial intelligence","level":2,"score":0.3147999942302704},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3116999864578247},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.31139999628067017},{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C188045654","wikidata":"https://www.wikidata.org/wiki/Q17148339","display_name":"Memory bandwidth","level":2,"score":0.30720001459121704},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30410000681877136},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.29910001158714294},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.28790000081062317},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C189783530","wikidata":"https://www.wikidata.org/wiki/Q352090","display_name":"CPU cache","level":3,"score":0.27720001339912415},{"id":"https://openalex.org/C19275194","wikidata":"https://www.wikidata.org/wiki/Q222903","display_name":"Multiplexing","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C176649486","wikidata":"https://www.wikidata.org/wiki/Q2308807","display_name":"Memory management","level":3,"score":0.25850000977516174},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25360000133514404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.11211","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.11211","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.11211","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.11211","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"popularity":[1],"of":[2,20,41,121],"large":[3],"language":[4],"models":[5],"(LLMs)":[6],"escalates":[7],"an":[8,165],"ongoing":[9],"demand":[10],"for":[11,87],"effective":[12],"inference.":[13,184],"However,":[14],"due":[15],"to":[16,35,162],"the":[17,23,30,42,89,131,153],"sequential":[18],"processing":[19],"tokens":[21],"during":[22,182],"token":[24,154],"phase":[25],"in":[26,91,152],"decoder-only":[27],"LLMs":[28],"inference,":[29],"inherent":[31],"low":[32],"parallelism":[33],"leads":[34],"reduced":[36],"throughput":[37],"and":[38,83,125,135],"suboptimal":[39],"utilization":[40,181],"computing":[43],"units":[44],"on":[45,94,130,164],"artificial":[46],"intelligence":[47],"(AI)":[48],"accelerators,":[49],"particularly":[50],"when":[51],"handling":[52],"long-sequence":[53],"inputs":[54],"that":[55,146],"impose":[56],"significant":[57],"memory":[58,112,150,179],"overhead.":[59],"Recently,":[60],"many":[61],"reported":[62],"methods":[63],"have":[64],"been":[65],"developed":[66],"as":[67,115,117],"potential":[68],"solutions,":[69],"since":[70],"they":[71],"emerge":[72],"with":[73,139,172],"numeric":[74],"deviation.":[75],"This":[76],"paper":[77],"presents":[78],"FastTPS,":[79],"a":[80,157],"high":[81],"performance":[82],"low-precision":[84],"loss":[85],"method":[86],"accelerating":[88],"token-phase":[90],"LLM":[92],"inference":[93],"general":[95],"AI":[96,104,168],"accelerators":[97],"which":[98,110],"includes":[99],"three":[100],"key":[101],"components:":[102],"(1)":[103],"accelerator-enabled":[105],"reloading-free":[106],"KV":[107],"Cache":[108],"concatenation":[109],"decreases":[111],"access":[113],"overhead":[114],"well":[116],"enables":[118],"full":[119],"fusion":[120],"Attention,":[122],"(2)":[123],"high-efficiency":[124],"high-accuracy":[126],"'RoPE'":[127],"attention":[128],"based":[129],"tiling":[132],"optimized":[133],"FLAT,":[134],"(3)":[136],"highly-fused":[137],"MLP":[138],"fine-grain":[140],"pipeline":[141],"scheduling.":[142],"Our":[143],"results":[144],"confirm":[145],"FastTPS":[147],"significantly":[148],"alleviates":[149],"bottlenecks":[151],"phase,":[155],"delivering":[156],"6x":[158],"speed":[159],"improvement":[160],"(compared":[161],"none-fusion)":[163],"AMD":[166],"Ryzen":[167],"300":[169],"series":[170],"NPU":[171],"BF16":[173],"precision":[174],"while":[175],"sustaining":[176],"93%":[177],"peak":[178],"bandwidth":[180],"Phi3-mini-4k-instruct":[183]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-15T00:00:00"}
