{"id":"https://openalex.org/W4226323948","doi":"https://doi.org/10.23919/date54114.2022.9774568","title":"DiGamma: Domain-aware Genetic Algorithm for HW-Mapping Co-optimization for DNN Accelerators","display_name":"DiGamma: Domain-aware Genetic Algorithm for HW-Mapping Co-optimization for DNN Accelerators","publication_year":2022,"publication_date":"2022-03-14","ids":{"openalex":"https://openalex.org/W4226323948","doi":"https://doi.org/10.23919/date54114.2022.9774568"},"language":"en","primary_location":{"id":"doi:10.23919/date54114.2022.9774568","doi":"https://doi.org/10.23919/date54114.2022.9774568","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date54114.2022.9774568","pdf_url":null,"source":{"id":"https://openalex.org/S4306418181","display_name":"Design, Automation, and Test in Europe","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2201.11220","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035130804","display_name":"Sheng-Chun Kao","orcid":"https://orcid.org/0000-0001-7928-9027","observed_orcids":["https://orcid.org/0000-0001-7928-9027"]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sheng-Chun Kao","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009910914","display_name":"Michael Pellauer","orcid":"https://orcid.org/0000-0002-5305-4307","observed_orcids":["https://orcid.org/0000-0002-5305-4307"]},"institutions":[{"id":"https://openalex.org/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]},{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Michael Pellauer","raw_affiliation_strings":["NVIDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024901904","display_name":"Angshuman Parashar","orcid":"https://orcid.org/0000-0001-9936-6501","observed_orcids":["https://orcid.org/0000-0001-9936-6501"]},"institutions":[{"id":"https://openalex.org/I1304085615","display_name":"Nvidia (United Kingdom)","ror":"https://ror.org/02kr42612","country_code":"GB","type":"company","lineage":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]},{"id":"https://openalex.org/I4210127875","display_name":"Nvidia (United States)","ror":"https://ror.org/03jdj4y14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210127875"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Angshuman Parashar","raw_affiliation_strings":["NVIDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NVIDIA","institution_ids":["https://openalex.org/I1304085615","https://openalex.org/I4210127875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034089074","display_name":"Tushar Krishna","orcid":"https://orcid.org/0000-0001-5738-6942","observed_orcids":["https://orcid.org/0000-0001-5738-6942"]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tushar Krishna","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.3099,"has_fulltext":true,"cited_by_count":30,"citation_normalized_percentile":{"value":0.96325088,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"232","last_page":"237"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10904","display_name":"Embedded Systems Design Techniques","score":0.45170000195503235,"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"}},"topics":[{"id":"https://openalex.org/T10904","display_name":"Embedded Systems Design Techniques","score":0.45170000195503235,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.4140999913215637,"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":0.0723000019788742,"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/dnn-accelerators","display_name":"DNN accelerators","score":0.9539999961853027},{"id":"https://openalex.org/keywords/hardware-mapping","display_name":"hardware mapping","score":0.640999972820282},{"id":"https://openalex.org/keywords/co-optimization","display_name":"co-optimization","score":0.9240000247955322},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"genetic algorithm","score":0.7910000085830688},{"id":"https://openalex.org/keywords/search-efficiency","display_name":"search efficiency","score":0.5360000133514404},{"id":"https://openalex.org/keywords/edge-computing","display_name":"edge computing","score":0.7889999747276306},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"cloud computing","score":0.953000009059906}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7472232580184937},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.7007572054862976},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.46090447902679443},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4564502239227295},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.45462727546691895},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.452610582113266},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.42721888422966003},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3504077196121216},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33472323417663574},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.2596292495727539},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24739515781402588},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14244070649147034},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.23919/date54114.2022.9774568","doi":"https://doi.org/10.23919/date54114.2022.9774568","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date54114.2022.9774568","pdf_url":null,"source":{"id":"https://openalex.org/S4306418181","display_name":"Design, Automation, and Test in Europe","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 Design, Automation &amp; Test in Europe Conference &amp; Exhibition (DATE)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2201.11220","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2201.11220","pdf_url":"https://arxiv.org/pdf/2201.11220","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2201.11220","doi":"https://doi.org/10.48550/arxiv.2201.11220","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2201.11220","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,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2201.11220","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2201.11220","pdf_url":"https://arxiv.org/pdf/2201.11220","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G5529443368","display_name":"OAC Core: SHF: Small: Enabling Rapid Design and Deployment of Deep Learning Models on Hardware Accelerators","funder_award_id":"1909900","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4226323948.pdf","grobid_xml":"https://content.openalex.org/works/W4226323948.grobid-xml"},"referenced_works_count":7,"referenced_works":["https://openalex.org/W2067523571","https://openalex.org/W2442974303","https://openalex.org/W2596367596","https://openalex.org/W2778749116","https://openalex.org/W3102790199","https://openalex.org/W3112293503","https://openalex.org/W3171752851"],"related_works":["https://openalex.org/W4408151378","https://openalex.org/W3112293503","https://openalex.org/W6989323237","https://openalex.org/W6990581671","https://openalex.org/W4389500432","https://openalex.org/W4280535785","https://openalex.org/W7203509340","https://openalex.org/W3191594941","https://openalex.org/W2921953552","https://openalex.org/W4280489237"],"abstract_inverted_index":{"The":[0],"design":[1,60],"of":[2,23,57],"DNN":[3],"accelerators":[4],"includes":[5],"two":[6],"key":[7],"parts:":[8],"HW":[9,64],"resource":[10],"configuration":[11],"and":[12,65,67,100,112],"mapping":[13],"strategy.":[14],"Intensive":[15],"research":[16],"has":[17],"been":[18],"conducted":[19],"to":[20,35,104],"optimize":[21],"each":[22],"them":[24],"independently.":[25],"Unfortunately,":[26],"optimizing":[27],"for":[28,77],"both":[29],"together":[30],"is":[31],"extremely":[32,37],"challenging":[33],"due":[34],"the":[36,58,105],"large":[38],"cross-coupled":[39],"search":[40,79],"space.":[41],"To":[42],"address":[43],"this,":[44],"in":[45,110],"this":[46],"paper,":[47],"we":[48],"propose":[49],"a":[50,68],"HW-Mapping":[51],"co-optimization":[52],"framework,":[53],"an":[54],"efficient":[55],"encoding":[56],"immense":[59],"space":[61],"constructed":[62],"by":[63],"Mapping,":[66],"domain-aware":[69],"genetic":[70],"algorithm,":[71],"named":[72],"DiGamma,":[73],"with":[74,84,89],"specialized":[75],"operators":[76],"improving":[78],"efficiency.":[80],"We":[81],"evaluate":[82],"DiGamma":[83,95],"seven":[85],"popular":[86],"DNNs":[87],"models":[88],"different":[90],"properties.":[91],"Our":[92],"evaluations":[93],"show":[94],"can":[96],"achieve":[97],"(geomean)":[98],"3.0x":[99],"10.0x":[101],"speedup,":[102],"comparing":[103],"best-performing":[106],"baseline":[107],"optimization":[108],"algorithms,":[109],"edge":[111],"cloud":[113],"settings.":[114]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":11},{"year":2022,"cited_by_count":3}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2022-05-05T00:00:00"}
