{"id":"https://openalex.org/W4413141583","doi":"https://doi.org/10.1145/3759918","title":"GINA: Exploiting Graph Neural Network Layer Features for Energy Efficient Inferencing in NVM-based PIM Accelerators","display_name":"GINA: Exploiting Graph Neural Network Layer Features for Energy Efficient Inferencing in NVM-based PIM Accelerators","publication_year":2025,"publication_date":"2025-08-11","ids":{"openalex":"https://openalex.org/W4413141583","doi":"https://doi.org/10.1145/3759918"},"language":"en","primary_location":{"id":"doi:10.1145/3759918","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3759918","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3759918","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":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3759918","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019597041","display_name":"Gaurav Narang","orcid":"https://orcid.org/0000-0001-9517-1280"},"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":"Gaurav Narang","raw_affiliation_strings":["Arizona State University","Arizona State University, Tempe, United States"],"raw_orcid":"https://orcid.org/0000-0001-9517-1280","affiliations":[{"raw_affiliation_string":"Arizona State University","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"Arizona State University, Tempe, United States","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024882425","display_name":"Chukwufumnanya Ogbogu","orcid":"https://orcid.org/0000-0002-8170-1161"},"institutions":[{"id":"https://openalex.org/I72951846","display_name":"Washington State University","ror":"https://ror.org/05dk0ce17","country_code":"US","type":"education","lineage":["https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chukwufumnanya Ogbogu","raw_affiliation_strings":["Washington State University","Washington State University, Pullman, United States"],"raw_orcid":"https://orcid.org/0000-0002-8170-1161","affiliations":[{"raw_affiliation_string":"Washington State University","institution_ids":["https://openalex.org/I72951846"]},{"raw_affiliation_string":"Washington State University, Pullman, United States","institution_ids":["https://openalex.org/I72951846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033021422","display_name":"Biresh Kumar Joardar","orcid":"https://orcid.org/0000-0002-7668-2824"},"institutions":[{"id":"https://openalex.org/I44461941","display_name":"University of Houston","ror":"https://ror.org/048sx0r50","country_code":"US","type":"education","lineage":["https://openalex.org/I44461941"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Biresh Kumar Joardar","raw_affiliation_strings":["University of Houston","University of Houston, Houston, United States"],"raw_orcid":"https://orcid.org/0000-0002-7668-2824","affiliations":[{"raw_affiliation_string":"University of Houston","institution_ids":["https://openalex.org/I44461941"]},{"raw_affiliation_string":"University of Houston, Houston, United States","institution_ids":["https://openalex.org/I44461941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055445718","display_name":"Janardhan Rao Doppa","orcid":"https://orcid.org/0000-0002-3848-5301"},"institutions":[{"id":"https://openalex.org/I72951846","display_name":"Washington State University","ror":"https://ror.org/05dk0ce17","country_code":"US","type":"education","lineage":["https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Janardhan Rao Doppa","raw_affiliation_strings":["Washington State University","Washington State University, Pullman, United States"],"raw_orcid":"https://orcid.org/0000-0002-3848-5301","affiliations":[{"raw_affiliation_string":"Washington State University","institution_ids":["https://openalex.org/I72951846"]},{"raw_affiliation_string":"Washington State University, Pullman, United States","institution_ids":["https://openalex.org/I72951846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033880864","display_name":"Krishnendu Chakrabarty","orcid":"https://orcid.org/0000-0003-4475-6435"},"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":"Krishnendu Chakrabarty","raw_affiliation_strings":["Arizona State University","Arizona State University, Tempe, United States"],"raw_orcid":"https://orcid.org/0000-0003-4475-6435","affiliations":[{"raw_affiliation_string":"Arizona State University","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"Arizona State University, Tempe, United States","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078441163","display_name":"Partha Pratim Pande","orcid":"https://orcid.org/0000-0002-5930-8531"},"institutions":[{"id":"https://openalex.org/I72951846","display_name":"Washington State University","ror":"https://ror.org/05dk0ce17","country_code":"US","type":"education","lineage":["https://openalex.org/I72951846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Partha Pratim Pande","raw_affiliation_strings":["Washington State University","Washington State University, Pullman, United States"],"raw_orcid":"https://orcid.org/0000-0002-5930-8531","affiliations":[{"raw_affiliation_string":"Washington State University","institution_ids":["https://openalex.org/I72951846"]},{"raw_affiliation_string":"Washington State University, Pullman, United States","institution_ids":["https://openalex.org/I72951846"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5141,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.68373735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"24","issue":"5s","first_page":"1","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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":1.0,"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":0.9997000098228455,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9962999820709229,"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":0.7873518466949463},{"id":"https://openalex.org/keywords/crossbar-switch","display_name":"Crossbar switch","score":0.7564489245414734},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5414950251579285},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.5054025650024414},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4744262099266052},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4578581750392914},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3796054422855377},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.35374361276626587},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.24607497453689575}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7873518466949463},{"id":"https://openalex.org/C29984679","wikidata":"https://www.wikidata.org/wiki/Q1929149","display_name":"Crossbar switch","level":2,"score":0.7564489245414734},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5414950251579285},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5054025650024414},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4744262099266052},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4578581750392914},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3796054422855377},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.35374361276626587},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.24607497453689575},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3759918","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3759918","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3759918","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"}],"best_oa_location":{"id":"doi:10.1145/3759918","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3759918","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3759918","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"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9100000262260437,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G2302397854","display_name":"FuSe-TG: Domain-Specific 3D ReRAM-based Processing-in-Memory Accelerators for Streaming Time Series Applications","funder_award_id":"2235398","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3977508544","display_name":"CSR: Small: Processing-in-Memory enabled Manycore Systems to Accelerate Graph Neural Network-based Data Analytics","funder_award_id":"2308530","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5001791597","display_name":null,"funder_award_id":"ARO-W911NF-24-1-0240","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G661180653","display_name":null,"funder_award_id":"CSR-2308530","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7452299184","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G8843100692","display_name":null,"funder_award_id":"2235398 (sub-award from University of California at Riverside) and CSR-2308530","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"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4413141583.pdf","grobid_xml":"https://content.openalex.org/works/W4413141583.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W569478347","https://openalex.org/W2062284372","https://openalex.org/W2070232376","https://openalex.org/W2104492856","https://openalex.org/W2118231264","https://openalex.org/W2164819109","https://openalex.org/W2329556826","https://openalex.org/W2518281301","https://openalex.org/W2519887557","https://openalex.org/W2581035600","https://openalex.org/W2613989746","https://openalex.org/W2624431344","https://openalex.org/W2725159389","https://openalex.org/W2913347375","https://openalex.org/W2945827377","https://openalex.org/W2946522000","https://openalex.org/W2949674408","https://openalex.org/W3017228913","https://openalex.org/W3021975806","https://openalex.org/W3042770487","https://openalex.org/W3091835145","https://openalex.org/W3092585568","https://openalex.org/W3093814892","https://openalex.org/W3099375322","https://openalex.org/W3101553402","https://openalex.org/W3110757807","https://openalex.org/W3111475881","https://openalex.org/W3111989171","https://openalex.org/W3134764339","https://openalex.org/W3139113149","https://openalex.org/W3171313724","https://openalex.org/W3201504383","https://openalex.org/W4205270231","https://openalex.org/W4213019189","https://openalex.org/W4280509186","https://openalex.org/W4293023446","https://openalex.org/W4293024097","https://openalex.org/W4312076514","https://openalex.org/W4312121117","https://openalex.org/W4360831816","https://openalex.org/W4367047347","https://openalex.org/W4376137878","https://openalex.org/W4378187530","https://openalex.org/W4383469260","https://openalex.org/W4385968202","https://openalex.org/W4386486836","https://openalex.org/W4386859265","https://openalex.org/W4392806407","https://openalex.org/W4394827161","https://openalex.org/W4396956635","https://openalex.org/W4405205359","https://openalex.org/W4410584219","https://openalex.org/W6799166919","https://openalex.org/W6805677314","https://openalex.org/W6852827097","https://openalex.org/W6856641747"],"related_works":["https://openalex.org/W2145932742","https://openalex.org/W1874409533","https://openalex.org/W2554791727","https://openalex.org/W1981395029","https://openalex.org/W2108083791","https://openalex.org/W4250137794","https://openalex.org/W2063341228","https://openalex.org/W2111673944","https://openalex.org/W2571519720","https://openalex.org/W3141540147"],"abstract_inverted_index":{"Graph":[0],"Neural":[1,250],"Networks":[2,251],"(GNNs)":[3],"are":[4,128],"made":[5],"up":[6],"of":[7,14,24,79,84,101,154,199,246],"multiple":[8],"layers,":[9],"with":[10,173],"each":[11],"layer":[12,137,177,201],"comprising":[13],"different":[15],"compute":[16],"kernels":[17],"involving":[18],"weight":[19],"vectors":[20],"and":[21,38,132,144,182,203,219,224,253],"adjacency":[22],"matrices":[23],"input":[25,183],"graph":[26,184],"dataset.":[27,185],"These":[28],"layers":[29,86,126],"exhibit":[30],"varying":[31],"features":[32,202],"such":[33,97],"as":[34,165,196],"sparsity,":[35],"storage":[36],"requirement,":[37],"impact":[39,100],"on":[40,104,227],"predictive":[41,70,105,239],"accuracy.":[42,71,240],"Non-volatile":[43],"memory":[44],"(NVM)-based":[45],"3D":[46,94,213],"Processing-In-Memory":[47],"(PIM)":[48],"architectures":[49,235],"offer":[50],"a":[51,81,93,111,134,152,161,197],"promising":[52],"approach":[53],"to":[54,87,121,138,145,164,188,232,248],"accelerate":[55],"GNN":[56,85,125,136,176,200],"inferencing.":[57],"However,":[58,169],"NVM":[59],"device-based":[60],"crossbars":[61],"suffer":[62],"from":[63],"various":[64],"non-idealities":[65,103,143],"that":[66,98,127,211],"affect":[67],"the":[68,77,99,124,149,155,174,190,217,238,244],"overall":[69],"In":[72],"this":[73],"work,":[74],"we":[75,242],"consider":[76],"problem":[78],"finding":[80],"suitable":[82,135],"mapping":[83],"PIM-based":[88],"processing":[89],"elements":[90],"(PEs)":[91],"in":[92,160],"manycore":[95],"architecture":[96,215],"crossbar":[102,150,157],"accuracy":[106,131],"is":[107,158],"minimized.":[108],"We":[109],"develop":[110],"framework":[112],"called":[113],"GINA,":[114],"which":[115],"leverages":[116],"low-cost,":[117],"approximate":[118],"Hessian-based":[119],"methodology":[120],"automatically":[122],"determine":[123],"critical":[129],"for":[130,193],"find":[133],"PE":[139],"mapping.":[140],"To":[141],"tackle":[142],"exploit":[146],"sparsity":[147],"at":[148],"level,":[151],"subset":[153],"full":[156],"activated":[159],"cycle,":[162],"referred":[163],"Operation":[166],"Unit":[167],"(OU).":[168],"OU":[170,191],"configurations":[171],"vary":[172],"above-mentioned":[175],"features,":[178],"time-dependent":[179,204],"conductance":[180,205],"drift,":[181],"GINA":[186,247],"learns":[187],"optimize":[189],"configuration":[192],"unseen":[194],"datasets":[195],"function":[198],"drift.":[206],"Our":[207],"experimental":[208],"results":[209],"demonstrate":[210,243],"GINA-enabled":[212],"PIM":[214,234],"reduces":[216],"latency":[218],"energy":[220],"by":[221],"7.4":[222],"imes":[223,226],"13":[225],"an":[228],"average,":[229],"respectively,":[230],"compared":[231],"state-of-the-art":[233],"without":[236],"compromising":[237],"Finally,":[241],"applicability":[245],"Convolutional":[249],"(CNNs)":[252],"Vision":[254],"Transformers.":[255]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-22T08:00:12.763002","created_date":"2025-10-10T00:00:00"}
