{"id":"https://openalex.org/W3195858150","doi":"https://doi.org/10.1145/3476999","title":"SIAM: Chiplet-based Scalable In-Memory Acceleration with Mesh for Deep Neural Networks","display_name":"SIAM: Chiplet-based Scalable In-Memory Acceleration with Mesh for Deep Neural Networks","publication_year":2021,"publication_date":"2021-09-17","ids":{"openalex":"https://openalex.org/W3195858150","doi":"https://doi.org/10.1145/3476999","mag":"3195858150"},"language":"en","primary_location":{"id":"doi:10.1145/3476999","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3476999","pdf_url":null,"source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions on Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Embedded Computing Systems","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2108.08903","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Gokul Krishnan","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Gokul Krishnan","raw_affiliation_strings":["Arizona State University, Tempe, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Sumit K. Mandal","orcid":null},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sumit K. Mandal","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, WI, USA"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Manvitha Pannala","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manvitha Pannala","raw_affiliation_strings":["Arizona State University, Tempe, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chaitali Chakrabarti","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chaitali Chakrabarti","raw_affiliation_strings":["Arizona State University, Tempe, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jae-Sun Seo","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jae-Sun Seo","raw_affiliation_strings":["Arizona State University, Tempe, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Umit Y. Ogras","orcid":null},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Umit Y. Ogras","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, WI, USA"],"affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yu Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu Cao","raw_affiliation_strings":["Arizona State University, Tempe, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":3.4539,"has_fulltext":false,"cited_by_count":56,"citation_normalized_percentile":{"value":0.93134261,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"20","issue":"5s","first_page":"1","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.5519999861717224,"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":0.5519999861717224,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.16990000009536743,"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":0.15860000252723694,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6917999982833862},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.6355999708175659},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6026999950408936},{"id":"https://openalex.org/keywords/interconnection","display_name":"Interconnection","score":0.5482000112533569},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5335999727249146},{"id":"https://openalex.org/keywords/dram","display_name":"Dram","score":0.5008999705314636},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.4392000138759613},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.42080000042915344}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7659000158309937},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6917999982833862},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.6773999929428101},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6355999708175659},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6026999950408936},{"id":"https://openalex.org/C123745756","wikidata":"https://www.wikidata.org/wiki/Q1665949","display_name":"Interconnection","level":2,"score":0.5482000112533569},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5335999727249146},{"id":"https://openalex.org/C7366592","wikidata":"https://www.wikidata.org/wiki/Q1255620","display_name":"Dram","level":2,"score":0.5008999705314636},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.4392000138759613},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.42080000042915344},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4171999990940094},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4099000096321106},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3944000005722046},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.37450000643730164},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36070001125335693},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3499000072479248},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.34299999475479126},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3328999876976013},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.3301999866962433},{"id":"https://openalex.org/C118021083","wikidata":"https://www.wikidata.org/wiki/Q610398","display_name":"System on a chip","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.2578999996185303},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2551000118255615},{"id":"https://openalex.org/C2776221188","wikidata":"https://www.wikidata.org/wiki/Q21072556","display_name":"Design space exploration","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3476999","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3476999","pdf_url":null,"source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions on Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Embedded Computing Systems","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2108.08903","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2108.08903","pdf_url":"https://arxiv.org/pdf/2108.08903","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2108.08903","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2108.08903","pdf_url":"https://arxiv.org/pdf/2108.08903","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"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":21,"referenced_works":["https://openalex.org/W2034861439","https://openalex.org/W2135407913","https://openalex.org/W2147657366","https://openalex.org/W2149935279","https://openalex.org/W2234584938","https://openalex.org/W2518281301","https://openalex.org/W2793528983","https://openalex.org/W2884166449","https://openalex.org/W2944987128","https://openalex.org/W2949989598","https://openalex.org/W2980104813","https://openalex.org/W2981124343","https://openalex.org/W2981985696","https://openalex.org/W3008954557","https://openalex.org/W3035560939","https://openalex.org/W3042495273","https://openalex.org/W3048606948","https://openalex.org/W3083443371","https://openalex.org/W3085277063","https://openalex.org/W3173065821","https://openalex.org/W4211178602"],"related_works":[],"abstract_inverted_index":{"In-memory":[0],"computing":[1,41],"(IMC)":[2],"on":[3,13,183],"a":[4,39,44,48,61,80,112,162],"monolithic":[5,49],"chip":[6],"for":[7,181],"deep":[8,55,116],"learning":[9,56],"faces":[10],"dramatic":[11],"challenges":[12],"area,":[14],"yield,":[15],"and":[16,74,96,125,127,139,152,176,191],"on-chip":[17],"interconnection":[18],"cost":[19],"due":[20],"to":[21,37,52,66,100,121,188],"the":[22,68,76,136,158,184],"ever-increasing":[23],"model":[24],"sizes.":[25],"2.5D":[26],"integration":[27],"or":[28],"chiplet-based":[29,71,168],"architectures":[30,73],"interconnect":[31],"multiple":[32],"small":[33],"chips":[34],"(i.e.,":[35],"chiplets)":[36],"form":[38],"large":[40,54],"system,":[42],"presenting":[43],"feasible":[45],"solution":[46],"beyond":[47],"IMC":[50,72,84,169],"architecture":[51,85,170],"accelerate":[53],"models.":[57],"This":[58],"paper":[59],"presents":[60],"new":[62],"benchmarking":[63,145],"simulator,":[64],"SIAM,":[65],"evaluate":[67],"performance":[69],"of":[70,78,111,115,129,142],"explore":[75],"potential":[77],"such":[79],"paradigm":[81],"shift":[82],"in":[83,108,179],"design.":[86],"SIAM":[87,105,143,173],"integrates":[88],"device,":[89],"circuit,":[90],"architecture,":[91],"network-on-chip":[92],"(NoC),":[93],"network-on-package":[94],"(NoP),":[95],"DRAM":[97],"access":[98],"models":[99],"realize":[101],"an":[102],"end-to-end":[103],"system.":[104],"is":[106],"scalable":[107],"its":[109],"support":[110],"wide":[113],"range":[114],"neural":[117],"networks":[118],"(DNNs),":[119],"customizable":[120],"various":[122],"network":[123],"structures":[124],"configurations,":[126],"capable":[128],"efficient":[130],"design":[131],"space":[132],"exploration.":[133],"We":[134,155],"demonstrate":[135],"flexibility,":[137],"scalability,":[138],"simulation":[140,159],"speed":[141],"by":[144],"different":[146],"state-of-the-art":[147],"DNNs":[148],"with":[149,161],"CIFAR-10,":[150],"CIFAR-100,":[151],"ImageNet":[153,185],"datasets.":[154],"further":[156],"calibrate":[157],"results":[160],"published":[163],"silicon":[164],"result,":[165],"SIMBA.":[166],"The":[167],"obtained":[171],"through":[172],"shows":[174],"130":[175],"72":[177],"improvement":[178],"energy-efficiency":[180],"ResNet-50":[182],"dataset":[186],"compared":[187],"Nvidia":[189],"V100":[190],"T4":[192],"GPUs.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":6}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2021-08-30T00:00:00"}