{"id":{"repo_id":"unm","oai_identifier":"oai:digitalrepository.unm.edu:ece_etds-1115"},"canonical_url":"https://search.dev.ndltd.org/etd/unm/oai:digitalrepository.unm.edu:ece_etds-1115","repository":{"repo_id":"unm","name":"University of New Mexico","base_url":"https://digitalrepository.unm.edu/do/oai/"},"display":{"title":"GPGPU-Enabled Physics Based Deformed Model Simulation","abstract":"Computer simulation techniques are widely adopted nowadays in many areas like manufacturing, engineering, graphics, animation, virtual reality and so on. However, the standard finite element based simulation is notorious for its expensive computation. To address this challenge, I present a GPU-based parallel implementation for simulating large elastic deformation. Classic modal analysis provides a set of orthonormal bases vectors, which span a spectral space encoding the dynamics of the elastic body. As each basis vector is orthogonal to each other, the computation is completely decoupled and can be well-fit into the modern GPGPU platform. We further explore the latest feature of NVIDIA CUDA so that the result of GPU computation can be directly used for upcoming rendering/visualization and a significant amount of overheads for transmitting data from client GPU and host CPU via the PCI-Express bus are avoided. Real-time simulation is made possible with this technique for many cases that otherwise is not possible.","abstract_html":"Computer simulation techniques are widely adopted nowadays in many areas like manufacturing, engineering, graphics, animation, virtual reality and so on. However, the standard finite element based simulation is notorious for its expensive computation. To address this challenge, I present a GPU-based parallel implementation for simulating large elastic deformation. Classic modal analysis provides a set of orthonormal bases vectors, which span a spectral space encoding the dynamics of the elastic body. As each basis vector is orthogonal to each other, the computation is completely decoupled and can be well-fit into the modern GPGPU platform. We further explore the latest feature of NVIDIA CUDA so that the result of GPU computation can be directly used for upcoming rendering/visualization and a significant amount of overheads for transmitting data from client GPU and host CPU via the PCI-Express bus are avoided. Real-time simulation is made possible with this technique for many cases that otherwise is not possible.","abstract_has_math":false,"creators":["Hernandez Samaniego, Alejandro Enedino"],"institution":null,"degree_name":"Computer Engineering","degree_level":"Thesis","degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":["Yang, Yin","Shu, Wei Wennie","Pattichis, Marios S."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-09-12T07:00:00Z","date_published":"2014-09-12T07:00:00Z","updated_at":"2026-07-24T05:27:19Z","subjects":["gpgpu","gpu","parallel","computing","deformed","simulation","object","model","cuda","parallelization"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalrepository.unm.edu/ece_etds/116","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Yang, Yin","Shu, Wei Wennie","Pattichis, Marios S."]},{"key":"dc:creator","label":"Author","values":["Hernandez Samaniego, Alejandro Enedino"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis","Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Computer Engineering"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["gpgpu","gpu","parallel","computing","deformed","simulation","object","model","cuda","parallelization"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalrepository.unm.edu/ece_etds/116"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Computer simulation techniques are widely adopted nowadays in many areas like manufacturing, engineering, graphics, animation, virtual reality and so on. However, the standard finite element based simulation is notorious for its expensive computation. To address this challenge, I present a GPU-based parallel implementation for simulating large elastic deformation. Classic modal analysis provides a set of orthonormal bases vectors, which span a spectral space encoding the dynamics of the elastic body. As each basis vector is orthogonal to each other, the computation is completely decoupled and can be well-fit into the modern GPGPU platform. We further explore the latest feature of NVIDIA CUDA so that the result of GPU computation can be directly used for upcoming rendering/visualization and a significant amount of overheads for transmitting data from client GPU and host CPU via the PCI-Express bus are avoided. Real-time simulation is made possible with this technique for many cases that otherwise is not possible."]},{"key":"dc:title","label":"Title","values":["GPGPU-Enabled Physics Based Deformed Model Simulation"]}]}],"canonical_facts":{"dc:contributor":["Yang, Yin","Shu, Wei Wennie","Pattichis, Marios S."],"dc:creator":["Hernandez Samaniego, Alejandro Enedino"],"dc:description.abstract":["Computer simulation techniques are widely adopted nowadays in many areas like manufacturing, engineering, graphics, animation, virtual reality and so on. However, the standard finite element based simulation is notorious for its expensive computation. To address this challenge, I present a GPU-based parallel implementation for simulating large elastic deformation. Classic modal analysis provides a set of orthonormal bases vectors, which span a spectral space encoding the dynamics of the elastic body. As each basis vector is orthogonal to each other, the computation is completely decoupled and can be well-fit into the modern GPGPU platform. We further explore the latest feature of NVIDIA CUDA so that the result of GPU computation can be directly used for upcoming rendering/visualization and a significant amount of overheads for transmitting data from client GPU and host CPU via the PCI-Express bus are avoided. Real-time simulation is made possible with this technique for many cases that otherwise is not possible."],"dc:identifier":["https://digitalrepository.unm.edu/ece_etds/116"],"dc:language":["English"],"dc:subject":["gpgpu","gpu","parallel","computing","deformed","simulation","object","model","cuda","parallelization"],"dc:title":["GPGPU-Enabled Physics Based Deformed Model Simulation"],"thesis:degree_discipline":["Electrical and Computer Engineering"],"thesis:degree_level":["Thesis","Masters"],"thesis:degree_name":["Computer Engineering"]},"updated_at":"2026-07-24T05:27:19Z"}