{"id":"https://openalex.org/W7160255579","doi":"https://doi.org/10.48550/arxiv.2605.01793","title":"Analytic Framework for Estimating Memory Cost","display_name":"Analytic Framework for Estimating Memory Cost","publication_year":2026,"publication_date":"2026-05-03","ids":{"openalex":"https://openalex.org/W7160255579","doi":"https://doi.org/10.48550/arxiv.2605.01793"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.01793","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01793","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.01793","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135370460","display_name":"Anirudh Shankar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shankar, Anirudh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135325396","display_name":"Avhishek Chatterjee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chatterjee, Avhishek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5013987317","display_name":"Anjan Chakravorty","orcid":"https://orcid.org/0000-0002-5253-8975"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chakravorty, Anjan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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/T12238","display_name":"Green IT and Sustainability","score":0.07410000264644623,"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/T12238","display_name":"Green IT and Sustainability","score":0.07410000264644623,"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/T10121","display_name":"Building Energy and Comfort Optimization","score":0.05849999934434891,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T14347","display_name":"Big Data and Digital Economy","score":0.045499999076128006,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/inference","display_name":"Inference","score":0.5206000208854675},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49619999527931213},{"id":"https://openalex.org/keywords/memory-footprint","display_name":"Memory footprint","score":0.484499990940094},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.3709999918937683},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.3330000042915344},{"id":"https://openalex.org/keywords/energy-cost","display_name":"Energy cost","score":0.3328999876976013}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7016000151634216},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5206000208854675},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49619999527931213},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4925999939441681},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.484499990940094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4514999985694885},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3709999918937683},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C3019966295","wikidata":"https://www.wikidata.org/wiki/Q1341368","display_name":"Energy cost","level":2,"score":0.3328999876976013},{"id":"https://openalex.org/C2780936489","wikidata":"https://www.wikidata.org/wiki/Q310667","display_name":"Carbon footprint","level":3,"score":0.33079999685287476},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2955000102519989},{"id":"https://openalex.org/C12186640","wikidata":"https://www.wikidata.org/wiki/Q6815743","display_name":"Memory model","level":3,"score":0.29420000314712524},{"id":"https://openalex.org/C157170001","wikidata":"https://www.wikidata.org/wiki/Q4781507","display_name":"Applications of artificial intelligence","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C132943942","wikidata":"https://www.wikidata.org/wiki/Q2562511","display_name":"Footprint","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.01793","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01793","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.01793","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.01793","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.49855199456214905}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"artificial":[1],"intelligence":[2],"(AI)":[3],"models":[4,33,38],"quickly":[5],"spread":[6],"and":[7,19,29,40],"become":[8],"more":[9],"advanced,":[10],"they":[11,59],"are":[12,45],"requiring":[13],"an":[14],"ever-increasing":[15],"amount":[16,56],"of":[17,31,57,87,94],"data":[18,62],"compute":[20],"capability,":[21],"leading":[22],"to":[23,47,53,78],"a":[24,48,69,84],"significant":[25],"energy":[26,75],"cost.":[27],"Training":[28],"inference":[30],"AI":[32],"including":[34],"the":[35,54,79,92],"large":[36,49],"language":[37],"(LLMs)":[39],"deep":[41],"neural":[42],"networks":[43],"(DNNs)":[44],"contributing":[46],"carbon":[50],"footprint":[51],"owing":[52],"massive":[55],"memory":[58],"consume":[60],"in":[61],"centers.":[63],"In":[64],"this":[65],"article,":[66],"we":[67],"present":[68],"generalized":[70],"framework":[71,82],"that":[72],"quantifies":[73],"these":[74],"costs":[76],"incurred":[77],"environment.":[80],"This":[81],"provides":[83],"foundational":[85],"quantification":[86],"AI's":[88],"ecological":[89],"footprint,":[90],"facilitating":[91],"development":[93],"sustainable":[95],"architectural":[96],"strategies":[97],"for":[98],"future":[99],"models.":[100]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-06T00:00:00"}
