{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/16472"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/16472","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Design and implementation of a floating point unit for rigel, a massively parallel accelerator","abstract":"Scientific applications rely heavily on floating point data types. Floating point operations are complex and require complicated hardware that is both area and power intensive. The emergence of massively parallel architectures like Rigel creates new challenges and poses new questions with respect to floating point support. The massively parallel aspect of Rigel places great emphasis on area efficient, low power designs. At the same time, Rigel is a general purpose accelerator and must provide high performance for a wide class of applications. This thesis presents an analysis of various floating point unit (FPU) components with respect to Rigel, and attempts to present a candidate design of an FPU that balances performance, area, and power and is suitable for massively parallel architectures like Rigel.","abstract_html":"Scientific applications rely heavily on floating point data types. Floating point operations are complex and require complicated hardware that is both area and power intensive. The emergence of massively parallel architectures like Rigel creates new challenges and poses new questions with respect to floating point support. The massively parallel aspect of Rigel places great emphasis on area efficient, low power designs. At the same time, Rigel is a general purpose accelerator and must provide high performance for a wide class of applications. This thesis presents an analysis of various floating point unit (FPU) components with respect to Rigel, and attempts to present a candidate design of an FPU that balances performance, area, and power and is suitable for massively parallel architectures like Rigel.","abstract_has_math":false,"creators":["Truty, Wojciech J."],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engineering","degree_department":null,"school":null,"contributors":["Patel, Sanjay J."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010-06-22T19:37:13Z","date_published":"2010-06-22T19:37:13Z","updated_at":"2026-07-22T22:25:09Z","subjects":["Floating point","Rigel","parallel","many core","multicore","processor","Accelerator","Floating point unit (FPU)","floating point unit","IEEE Standard for Floating-Point Arithmetic (IEEE 754)","Massively parallel"],"languages":["en"],"rights":["Copyright 2010 Wojciech Truty"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/16472","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Patel, Sanjay J."]},{"key":"dc:creator","label":"Author","values":["Truty, Wojciech J."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2010-06-22T19:37:13Z","2010-5"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Floating point","Rigel","parallel","many core","multicore","processor","Accelerator","Floating point unit (FPU)","floating point unit","IEEE Standard for Floating-Point Arithmetic (IEEE 754)","Massively parallel"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2010 Wojciech Truty"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/16472"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Scientific applications rely heavily on floating point data types. Floating point operations are complex and require complicated hardware that is both area and power intensive. The emergence of massively parallel architectures like Rigel creates new challenges and poses new questions with respect to floating point support. The massively parallel aspect of Rigel places great emphasis on area efficient, low power designs. At the same time, Rigel is a general purpose accelerator and must provide high performance for a wide class of applications. 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