{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/83194"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/83194","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A Scalable Parallel Multigrid Solver for Three Dimensional Adaptive Mesh Structural Analysis","abstract":"A parallel multigrid algorithm for solution of adaptive structural analysis meshes (ParMASA) is described. The user inputs a coarse mesh. The coarse mesh is successively solved, error estimated, and refined. The refinement simultaneously reduces discretization error and creates a hierarchy of meshes for use by the multigrid solver. The mesh may be refined in an arbitrarily irregular anisotropic manner. A block data structure is implemented to facilitate the parallelization of this complex refinement algorithm. For parallel runs an efficient algorithm must have balanced load in all algorithm steps. In addition communication must be minimized. A variety of procedures to optimize parallel performance by modifying the structure of multigrid cycle, smoothers, and communication patterns are discussed. Benefits of the advanced refinement and efficient parallelization are discussed. Good speedups to hundreds of processors are obtained on an SGI Origin 2000. ParMASA shows excellent performance a 256 processor SGI Origin 2000. ParMASA can perform all required IO, refinement, error estimation, and solution steps of an over 10 million degree-of-freedom system of equations in only 142 seconds.","abstract_html":"A parallel multigrid algorithm for solution of adaptive structural analysis meshes (ParMASA) is described. The user inputs a coarse mesh. The coarse mesh is successively solved, error estimated, and refined. The refinement simultaneously reduces discretization error and creates a hierarchy of meshes for use by the multigrid solver. The mesh may be refined in an arbitrarily irregular anisotropic manner. A block data structure is implemented to facilitate the parallelization of this complex refinement algorithm. For parallel runs an efficient algorithm must have balanced load in all algorithm steps. In addition communication must be minimized. A variety of procedures to optimize parallel performance by modifying the structure of multigrid cycle, smoothers, and communication patterns are discussed. Benefits of the advanced refinement and efficient parallelization are discussed. Good speedups to hundreds of processors are obtained on an SGI Origin 2000. ParMASA shows excellent performance a 256 processor SGI Origin 2000. ParMASA can perform all required IO, refinement, error estimation, and solution steps of an over 10 million degree-of-freedom system of equations in only 142 seconds.","abstract_has_math":false,"creators":["Crane, Nathan Karl"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Hjelmstad, Keith D.","Parsons, I.D."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-25T21:03:29Z","date_published":"2015-09-25T21:03:29Z","updated_at":"2026-07-22T22:26:20Z","subjects":["Computer Science"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3070285"],"render_values":[{"text":"(MiAaPQ)AAI3070285","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/83194","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hjelmstad, Keith D.","Parsons, I.D."]},{"key":"dc:creator","label":"Author","values":["Crane, Nathan Karl"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-25T21:03:29Z","10000-01-01","2002"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"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":["Computer Science"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/83194","(MiAaPQ)AAI3070285"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["A parallel multigrid algorithm for solution of adaptive structural analysis meshes (ParMASA) is described. The user inputs a coarse mesh. The coarse mesh is successively solved, error estimated, and refined. The refinement simultaneously reduces discretization error and creates a hierarchy of meshes for use by the multigrid solver. The mesh may be refined in an arbitrarily irregular anisotropic manner. A block data structure is implemented to facilitate the parallelization of this complex refinement algorithm. For parallel runs an efficient algorithm must have balanced load in all algorithm steps. In addition communication must be minimized. A variety of procedures to optimize parallel performance by modifying the structure of multigrid cycle, smoothers, and communication patterns are discussed. Benefits of the advanced refinement and efficient parallelization are discussed. Good speedups to hundreds of processors are obtained on an SGI Origin 2000. ParMASA shows excellent performance a 256 processor SGI Origin 2000. ParMASA can perform all required IO, refinement, error estimation, and solution steps of an over 10 million degree-of-freedom system of equations in only 142 seconds.","Made available in DSpace on 2015-09-25T21:03:29Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3070285.pdf: 10326251 bytes, checksum: 1fcc3d79cb9c2e3888c882faeece6f27 (MD5) Previous issue date: 2002","Embargo set by: Seth Robbins for item 84475 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","266 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002."]},{"key":"dc:title","label":"Title","values":["A Scalable Parallel Multigrid Solver for Three Dimensional Adaptive Mesh Structural Analysis"]}]}],"canonical_facts":{"dc:contributor":["Hjelmstad, Keith D.","Parsons, I.D."],"dc:creator":["Crane, Nathan Karl"],"dc:date":["2015-09-25T21:03:29Z","10000-01-01","2002"],"dc:description":["A parallel multigrid algorithm for solution of adaptive structural analysis meshes (ParMASA) is described. The user inputs a coarse mesh. The coarse mesh is successively solved, error estimated, and refined. The refinement simultaneously reduces discretization error and creates a hierarchy of meshes for use by the multigrid solver. The mesh may be refined in an arbitrarily irregular anisotropic manner. A block data structure is implemented to facilitate the parallelization of this complex refinement algorithm. For parallel runs an efficient algorithm must have balanced load in all algorithm steps. In addition communication must be minimized. A variety of procedures to optimize parallel performance by modifying the structure of multigrid cycle, smoothers, and communication patterns are discussed. Benefits of the advanced refinement and efficient parallelization are discussed. Good speedups to hundreds of processors are obtained on an SGI Origin 2000. ParMASA shows excellent performance a 256 processor SGI Origin 2000. ParMASA can perform all required IO, refinement, error estimation, and solution steps of an over 10 million degree-of-freedom system of equations in only 142 seconds.","Made available in DSpace on 2015-09-25T21:03:29Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3070285.pdf: 10326251 bytes, checksum: 1fcc3d79cb9c2e3888c882faeece6f27 (MD5) Previous issue date: 2002","Embargo set by: Seth Robbins for item 84475 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","266 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002."],"dc:identifier":["http://hdl.handle.net/2142/83194","(MiAaPQ)AAI3070285"],"dc:language":["eng"],"dc:subject":["Computer Science"],"dc:title":["A Scalable Parallel Multigrid Solver for Three Dimensional Adaptive Mesh Structural Analysis"],"dc:type":["text"],"thesis:degree_discipline":["Civil Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:20Z"}