{"id":"https://openalex.org/W4416756241","doi":"https://doi.org/10.1109/ojcas.2025.3589132","title":"MARVEL: An End-to-End Framework for Generating Model-Class Aware Custom RISC-V Extensions for Lightweight AI","display_name":"MARVEL: An End-to-End Framework for Generating Model-Class Aware Custom RISC-V Extensions for Lightweight AI","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416756241","doi":"https://doi.org/10.1109/ojcas.2025.3589132"},"language":"en","primary_location":{"id":"doi:10.1109/ojcas.2025.3589132","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcas.2025.3589132","pdf_url":null,"source":{"id":"https://openalex.org/S4210192473","display_name":"IEEE Open Journal of Circuits and Systems","issn_l":"2644-1225","issn":["2644-1225"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Open Journal of Circuits and Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/ojcas.2025.3589132","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102736200","display_name":"Ajay Kumar M","orcid":"https://orcid.org/0000-0002-2878-1537"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"M. Ajay Kumar","raw_affiliation_strings":["School of Electrical and Electronic Engineering, University College Dublin, Dublin 4, Ireland"],"raw_orcid":"https://orcid.org/0000-0002-2878-1537","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, University College Dublin, Dublin 4, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020705180","display_name":"Caroline A. O'Mahoney","orcid":"https://orcid.org/0009-0002-9218-5171"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Cian O\u2019Mahoney","raw_affiliation_strings":["School of Electrical and Electronic Engineering, University College Dublin, Dublin 4, Ireland"],"raw_orcid":"https://orcid.org/0009-0002-9218-5171","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, University College Dublin, Dublin 4, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120523342","display_name":"Pedro Kreutz Werle","orcid":null},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Pedro Kreutz Werle","raw_affiliation_strings":["School of Electrical and Electronic Engineering, University College Dublin, Dublin 4, Ireland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, University College Dublin, Dublin 4, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065729450","display_name":"Shanker Shreejith","orcid":"https://orcid.org/0000-0002-9717-1804"},"institutions":[{"id":"https://openalex.org/I205274468","display_name":"Trinity College Dublin","ror":"https://ror.org/02tyrky19","country_code":"IE","type":"education","lineage":["https://openalex.org/I205274468"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Shreejith Shanker","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Trinity College Dublin, Dublin 4, Ireland"],"raw_orcid":"https://orcid.org/0000-0002-9717-1804","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Trinity College Dublin, Dublin 4, Ireland","institution_ids":["https://openalex.org/I205274468"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005410613","display_name":"Dimitrios S. Nikolopoulos","orcid":"https://orcid.org/0000-0003-0217-8307"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dimitrios S. Nikolopoulos","raw_affiliation_strings":["State University Global Change Center, Virginia Tech, Blacksburg, VA, USA"],"raw_orcid":"https://orcid.org/0000-0003-0217-8307","affiliations":[{"raw_affiliation_string":"State University Global Change Center, Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040279482","display_name":"Bo Ji","orcid":"https://orcid.org/0000-0003-0149-7509"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Ji","raw_affiliation_strings":["State University Global Change Center, Virginia Tech, Blacksburg, VA, USA"],"raw_orcid":"https://orcid.org/0000-0003-0149-7509","affiliations":[{"raw_affiliation_string":"State University Global Change Center, Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086758775","display_name":"Hans Vandierendonck","orcid":"https://orcid.org/0000-0001-5868-9259"},"institutions":[{"id":"https://openalex.org/I126231945","display_name":"Queen's University Belfast","ror":"https://ror.org/00hswnk62","country_code":"GB","type":"education","lineage":["https://openalex.org/I126231945"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hans Vandierendonck","raw_affiliation_strings":["Faculty of Engineering and Physical Sciences, Queen&#x2019;s University Belfast, Belfast, U.K"],"raw_orcid":"https://orcid.org/0000-0001-5868-9259","affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Physical Sciences, Queen&#x2019;s University Belfast, Belfast, U.K","institution_ids":["https://openalex.org/I126231945"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029098934","display_name":"Deepu John","orcid":"https://orcid.org/0000-0002-6139-1100"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Deepu John","raw_affiliation_strings":["School of Electrical and Electronic Engineering, University College Dublin, Dublin 4, Ireland"],"raw_orcid":"https://orcid.org/0000-0002-6139-1100","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, University College Dublin, Dublin 4, Ireland","institution_ids":["https://openalex.org/I100930933"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1750,"currency":"USD","value_usd":1750},"apc_paid":{"value":1750,"currency":"USD","value_usd":1750},"fwci":0.7655,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.77753366,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"6","issue":null,"first_page":"445","last_page":"456"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.7797999978065491,"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":0.7797999978065491,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.06960000097751617,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.03020000085234642,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.718500018119812},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.5587999820709229},{"id":"https://openalex.org/keywords/compiler","display_name":"Compiler","score":0.5382000207901001},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.47859999537467957},{"id":"https://openalex.org/keywords/design-flow","display_name":"Design flow","score":0.4302000105381012},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.4293999969959259},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.42669999599456787},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.424699991941452},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.41850000619888306},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41200000047683716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.817799985408783},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.718500018119812},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.5680999755859375},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.5587999820709229},{"id":"https://openalex.org/C169590947","wikidata":"https://www.wikidata.org/wiki/Q47506","display_name":"Compiler","level":2,"score":0.5382000207901001},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.47859999537467957},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.46619999408721924},{"id":"https://openalex.org/C37135326","wikidata":"https://www.wikidata.org/wiki/Q931942","display_name":"Design flow","level":2,"score":0.4302000105381012},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.4293999969959259},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42669999599456787},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.424699991941452},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.41850000619888306},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41200000047683716},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4043999910354614},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.40299999713897705},{"id":"https://openalex.org/C78766204","wikidata":"https://www.wikidata.org/wiki/Q555032","display_name":"Multi-core processor","level":2,"score":0.3799000084400177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37040001153945923},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36660000681877136},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.35120001435279846},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C36941000","wikidata":"https://www.wikidata.org/wiki/Q209455","display_name":"VHDL","level":3,"score":0.32839998602867126},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3203999996185303},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.30169999599456787},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2992999851703644},{"id":"https://openalex.org/C3020431745","wikidata":"https://www.wikidata.org/wiki/Q25325220","display_name":"Many core","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C2777575374","wikidata":"https://www.wikidata.org/wiki/Q1644704","display_name":"MicroBlaze","level":3,"score":0.29420000314712524},{"id":"https://openalex.org/C26771161","wikidata":"https://www.wikidata.org/wiki/Q16980","display_name":"ARM architecture","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C58013763","wikidata":"https://www.wikidata.org/wiki/Q5754574","display_name":"High-level synthesis","level":3,"score":0.28790000081062317},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.2831999957561493},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2825999855995178},{"id":"https://openalex.org/C142962650","wikidata":"https://www.wikidata.org/wiki/Q240838","display_name":"Reconfigurable computing","level":3,"score":0.26600000262260437},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C2776928060","wikidata":"https://www.wikidata.org/wiki/Q1753563","display_name":"SystemC","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.2558000087738037},{"id":"https://openalex.org/C154488198","wikidata":"https://www.wikidata.org/wiki/Q1335007","display_name":"Embedded software","level":3,"score":0.2547999918460846},{"id":"https://openalex.org/C489000","wikidata":"https://www.wikidata.org/wiki/Q747385","display_name":"Data flow diagram","level":2,"score":0.2531000077724457},{"id":"https://openalex.org/C2780395129","wikidata":"https://www.wikidata.org/wiki/Q1128971","display_name":"Rapid prototyping","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ojcas.2025.3589132","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcas.2025.3589132","pdf_url":null,"source":{"id":"https://openalex.org/S4210192473","display_name":"IEEE Open Journal of Circuits and Systems","issn_l":"2644-1225","issn":["2644-1225"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Open Journal of Circuits and Systems","raw_type":"journal-article"},{"id":"pmh:oai:pure.qub.ac.uk/portal:publications/5d5d2f62-b94c-4849-a2e0-af4ec0baf65c","is_oa":true,"landing_page_url":"https://pure.qub.ac.uk/en/publications/5d5d2f62-b94c-4849-a2e0-af4ec0baf65c","pdf_url":null,"source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Kumar, M A, O'Mahoney, C, Werle, P K, Shanker, S, Nikolopoulos, D S, Ji, B, Vandierendonck, H & John, D 2025, 'MARVEL: an end-to-end framework for generating model-class aware custom RISC-V extensions for lightweight AI', IEEE Open Journal of Circuits and Systems, vol. 6, pp. 445-456. https://doi.org/10.1109/OJCAS.2025.3589132","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:07c6d89c98044833b4fb4eb460b04e4d","is_oa":true,"landing_page_url":"https://doaj.org/article/07c6d89c98044833b4fb4eb460b04e4d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Open Journal of Circuits and Systems, Vol 6, Pp 445-456 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/ojcas.2025.3589132","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ojcas.2025.3589132","pdf_url":null,"source":{"id":"https://openalex.org/S4210192473","display_name":"IEEE Open Journal of Circuits and Systems","issn_l":"2644-1225","issn":["2644-1225"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Open Journal of Circuits and Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3298831798","display_name":null,"funder_award_id":"18/CRT/6183","funder_id":"https://openalex.org/F4320310641","funder_display_name":"National Centre for Groundwater Research and Training"},{"id":"https://openalex.org/G7767368729","display_name":null,"funder_award_id":"22/US/3848","funder_id":"https://openalex.org/F8766430056","funder_display_name":"Research Ireland"},{"id":"https://openalex.org/G8515454090","display_name":"Collaborative Research: CNS Core: Medium:HardLambda: A new FaaS Abstraction for Cross-Stack Resource Management in Disaggregated Datacenters","funder_award_id":"2106634","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/F4320310641","display_name":"National Centre for Groundwater Research and Training","ror":"https://ror.org/0087v5134"},{"id":"https://openalex.org/F4320316531","display_name":"Department for the Economy","ror":"https://ror.org/0161w0r98"},{"id":"https://openalex.org/F8766430056","display_name":"Research Ireland","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2138011018","https://openalex.org/W2289252105","https://openalex.org/W2804032941","https://openalex.org/W2963255460","https://openalex.org/W3027324516","https://openalex.org/W3036554530","https://openalex.org/W3184606595","https://openalex.org/W3194490872","https://openalex.org/W3198035615","https://openalex.org/W4205412054","https://openalex.org/W4224228206","https://openalex.org/W4283322959","https://openalex.org/W4322761281","https://openalex.org/W4385585360","https://openalex.org/W4386952738","https://openalex.org/W4392581122","https://openalex.org/W4393405582","https://openalex.org/W4399723198","https://openalex.org/W4401308326","https://openalex.org/W4404057186","https://openalex.org/W4404484626","https://openalex.org/W4408144859"],"related_works":[],"abstract_inverted_index":{"Deploying":[0],"deep":[1],"neural":[2,77],"networks":[3,78],"(DNNs)":[4],"on":[5,75,167,183,239],"resource-constrained":[6,177],"IoT":[7,38],"devices":[8],"remains":[9],"a":[10,72,129,140,203,207,233],"challenging":[11],"problem,":[12],"often":[13],"requiring":[14],"hardware":[15],"modifications":[16],"tailored":[17,65],"to":[18,66],"individual":[19],"AI":[20],"models.":[21],"Existing":[22],"accelerator-generation":[23],"tools,":[24],"such":[25,187],"as":[26,188,202],"AMD\u2019s":[27],"FINN,":[28],"do":[29],"not":[30],"adequately":[31],"address":[32],"extreme":[33],"resource":[34],"limitations":[35],"faced":[36],"by":[37],"endpoints":[39],"operating":[40,46],"in":[41,87,175,216,228],"bare-metal":[42,149],"environments":[43],"without":[44],"an":[45,91,147,156,240],"system":[47],"(OS).":[48],"To":[49],"overcome":[50],"these":[51],"constraints,":[52],"we":[53],"propose":[54],"MARVEL\u2013an":[55],"automated,":[56],"end-to-end":[57],"framework":[58],"that":[59],"generates":[60,90],"custom":[61,130],"RISC-V":[62,93,131,200],"ISA":[63],"extensions":[64],"specific":[67,142],"DNN":[68,85,112,185],"model":[69],"classes,":[70],"with":[71,95],"primary":[73],"focus":[74],"convolutional":[76],"(CNNs).":[79],"The":[80,102],"proposed":[81],"method":[82],"profiles":[83],"high-level":[84,110],"representations":[86],"Python":[88],"and":[89,127,132,194,218],"ISA-extended":[92],"core":[94,201],"associated":[96],"compiler":[97],"tools":[98],"for":[99,108,122,136,155],"efficient":[100],"deployment.":[101],"flow":[103,182],"leverages":[104],"(1)":[105],"Apache":[106],"TVM":[107],"translating":[109],"Python-based":[111],"models":[113,186],"into":[114],"optimized":[115,148],"C":[116,150],"code,":[117],"(2)":[118],"Synopsys":[119,198],"ASIP":[120],"Designer":[121],"identifying":[123],"compute-intensive":[124],"kernels,":[125],"modeling,":[126],"generating":[128],"(3)":[133],"Xilinx":[134],"Vivado":[135],"FPGA":[137,245],"implementation.":[138],"Beyond":[139],"model-class":[141],"RISC-V,":[143],"our":[144,170],"approach":[145],"produces":[146],"implementation,":[151],"eliminating":[152],"the":[153,181,197],"need":[154],"OS":[157],"or":[158],"extensive":[159],"software":[160],"dependencies.":[161],"Unlike":[162],"conventional":[163],"deployment":[164],"pipelines":[165],"relying":[166],"TensorFlow/PyTorch":[168],"runtimes,":[169],"solution":[171],"enables":[172],"seamless":[173],"execution":[174],"highly":[176],"environments.":[178],"We":[179],"evaluated":[180],"popular":[184],"LeNet-5*,":[189],"MobileNetV1,":[190],"ResNet50,":[191],"VGG16,":[192],"MobileNetV2":[193],"DenseNet121":[195],"using":[196],"trv32p3":[199],"baseline.":[204],"Results":[205],"show":[206],"<inline-formula":[208,220],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[209,221],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[210,222],"<tex-math":[211,223],"notation=\"LaTeX\">$2\\times":[212,224],"$":[213,225],"</tex-math></inline-formula>":[214,226],"speedup":[215],"inference":[217,231],"upto":[219],"reduction":[227],"energy":[229],"per":[230],"at":[232],"28.23%":[234],"area":[235],"overhead":[236],"when":[237],"implemented":[238],"AMD":[241],"Zynq":[242],"UltraScale+":[243],"ZCU104":[244],"platform.":[246]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-06T06:03:25.996018","created_date":"2025-11-25T00:00:00"}