{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/88935"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/88935","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A comparative study of shared memory parallelism on regular and irregular data structures using OpenMP and Galois","abstract":"Task and/or data parallelism can be exploited in most applications on today's multi-core processors. However, inefficient data organization, data dependencies, and hardware constraints limit scalable parallelization of these applications. In this thesis, performance and the impact of some optimizations is compared and evaluated for simple tasks using two parallel frameworks, OpenMP and Galois. Additionally, their performance on three real life applications, High Accuracy Relativistic Magnetohydrodynamics (HARM) which operates on a grid data structure; Delaunay Triangulation, which refines a triangulated mesh; and Dynamic Fracture Propagation, which operates on a triangulated mesh with adaptive refinement; is evaluated. It is found that OpenMP is a simple yet powerful tool for parallelization of most regular applications and workloads. Galois, which is specially designed for irregular data patterns, performs well for graph like structures. However, neither of them are well suited for all tasks and other frameworks must be explored to find one that is simple to use and yet powerful for all possible applications.","abstract_html":"Task and/or data parallelism can be exploited in most applications on today's multi-core processors. However, inefficient data organization, data dependencies, and hardware constraints limit scalable parallelization of these applications. In this thesis, performance and the impact of some optimizations is compared and evaluated for simple tasks using two parallel frameworks, OpenMP and Galois. Additionally, their performance on three real life applications, High Accuracy Relativistic Magnetohydrodynamics (HARM) which operates on a grid data structure; Delaunay Triangulation, which refines a triangulated mesh; and Dynamic Fracture Propagation, which operates on a triangulated mesh with adaptive refinement; is evaluated. It is found that OpenMP is a simple yet powerful tool for parallelization of most regular applications and workloads. Galois, which is specially designed for irregular data patterns, performs well for graph like structures. However, neither of them are well suited for all tasks and other frameworks must be explored to find one that is simple to use and yet powerful for all possible applications.","abstract_has_math":false,"creators":["Pothukuchi, Sweta Yamini"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Padua, David"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-03-02T19:32:54Z","date_published":"2016-03-02T19:32:54Z","updated_at":"2026-07-22T22:26:32Z","subjects":["parallel","OpenMP","Galois"],"languages":["en"],"rights":["Copyright 2015 Sweta Yamini Pothukuchi"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/88935","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Padua, David"]},{"key":"dc:creator","label":"Author","values":["Pothukuchi, Sweta Yamini"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2016-03-02T19:32:54Z","2015-08-19","2015-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"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":["parallel","OpenMP","Galois"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2015 Sweta Yamini Pothukuchi"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/88935"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Task and/or data parallelism can be exploited in most applications on today's multi-core processors. However, inefficient data organization, data dependencies, and hardware constraints limit scalable parallelization of these applications. In this thesis, performance and the impact of some optimizations is compared and evaluated for simple tasks using two parallel frameworks, OpenMP and Galois. Additionally, their performance on three real life applications, High Accuracy Relativistic Magnetohydrodynamics (HARM) which operates on a grid data structure; Delaunay Triangulation, which refines a triangulated mesh; and Dynamic Fracture Propagation, which operates on a triangulated mesh with adaptive refinement; is evaluated. It is found that OpenMP is a simple yet powerful tool for parallelization of most regular applications and workloads. Galois, which is specially designed for irregular data patterns, performs well for graph like structures. However, neither of them are well suited for all tasks and other frameworks must be explored to find one that is simple to use and yet powerful for all possible applications.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-03-02 without embargo terms","The student, Sweta Pothukuchi, accepted the attached license on 2015-08-17 at 15:47.","The student, Sweta Pothukuchi, submitted this Thesis for approval on 2015-08-17 at 15:49.","This Thesis was approved for publication on 2015-08-19 at 14:32.","DSpace SAF Submission Ingestion Package generated from Vireo submission #8662 on 2016-03-02 at 12:48:48","Made available in DSpace on 2016-03-02T19:32:54Z (GMT). No. of bitstreams: 2 POTHUKUCHI-THESIS-2015.pdf: 7771611 bytes, checksum: f6ae9851662ad604177e83dd5751bb12 (MD5) LICENSE.txt: 4213 bytes, checksum: 706add1a2966a0d1158250f0b49ebe8d (MD5) Previous issue date: 2015-08-19"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["A comparative study of shared memory parallelism on regular and irregular data structures using OpenMP and Galois"]}]}],"canonical_facts":{"dc:contributor":["Padua, David"],"dc:creator":["Pothukuchi, Sweta Yamini"],"dc:date":["2016-03-02T19:32:54Z","2015-08-19","2015-12"],"dc:description":["Task and/or data parallelism can be exploited in most applications on today's multi-core processors. However, inefficient data organization, data dependencies, and hardware constraints limit scalable parallelization of these applications. In this thesis, performance and the impact of some optimizations is compared and evaluated for simple tasks using two parallel frameworks, OpenMP and Galois. Additionally, their performance on three real life applications, High Accuracy Relativistic Magnetohydrodynamics (HARM) which operates on a grid data structure; Delaunay Triangulation, which refines a triangulated mesh; and Dynamic Fracture Propagation, which operates on a triangulated mesh with adaptive refinement; is evaluated. It is found that OpenMP is a simple yet powerful tool for parallelization of most regular applications and workloads. Galois, which is specially designed for irregular data patterns, performs well for graph like structures. However, neither of them are well suited for all tasks and other frameworks must be explored to find one that is simple to use and yet powerful for all possible applications.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-03-02 without embargo terms","The student, Sweta Pothukuchi, accepted the attached license on 2015-08-17 at 15:47.","The student, Sweta Pothukuchi, submitted this Thesis for approval on 2015-08-17 at 15:49.","This Thesis was approved for publication on 2015-08-19 at 14:32.","DSpace SAF Submission Ingestion Package generated from Vireo submission #8662 on 2016-03-02 at 12:48:48","Made available in DSpace on 2016-03-02T19:32:54Z (GMT). No. of bitstreams: 2 POTHUKUCHI-THESIS-2015.pdf: 7771611 bytes, checksum: f6ae9851662ad604177e83dd5751bb12 (MD5) LICENSE.txt: 4213 bytes, checksum: 706add1a2966a0d1158250f0b49ebe8d (MD5) Previous issue date: 2015-08-19"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/88935"],"dc:language":["en"],"dc:rights":["Copyright 2015 Sweta Yamini Pothukuchi"],"dc:subject":["parallel","OpenMP","Galois"],"dc:title":["A comparative study of shared memory parallelism on regular and irregular data structures using OpenMP and Galois"],"dc:type":["text"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:32Z"}