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dc.contributor.advisorChow, Edmond
dc.contributor.authorLiu, Xing
dc.date.accessioned2015-06-08T18:20:22Z
dc.date.available2015-06-08T18:20:22Z
dc.date.created2015-05
dc.date.issued2014-12-17
dc.date.submittedMay 2015
dc.identifier.urihttp://hdl.handle.net/1853/53487
dc.description.abstractMolecular simulation is an indispensable tool in many different disciplines such as physics, biology, chemical engineering, materials science, drug design, and others. Performing large-scale molecular simulation is of great interest to biologists and chemists, because many important biological and pharmaceutical phenomena can only be observed in very large molecule systems and after sufficiently long time dynamics. On the other hand, molecular simulation methods usually have very steep computational costs, which limits current molecular simulation studies to relatively small systems. The gap between the scale of molecular simulation that existing techniques can handle and the scale of interest has become a major barrier for applying molecular simulation to study real-world problems. In order to study large-scale molecular systems using molecular simulation, it requires developing highly parallel simulation algorithms and constantly adapting the algorithms to rapidly changing high performance computing architectures. However, many existing algorithms and codes for molecular simulation are from more than a decade ago, which were designed for sequential computers or early parallel architectures. They may not scale efficiently and do not fully exploit features of today's hardware. Given the rapid evolution in computer architectures, the time has come to revisit these molecular simulation algorithms and codes. In this thesis, we demonstrate our approach to addressing the computational challenges of large-scale molecular simulation by presenting both the high-performance algorithms and software for two important molecular simulation applications: Hartree-Fock (HF) calculations and hydrodynamics simulations, on highly parallel computer architectures. The algorithms and software presented in this thesis have been used by biologists and chemists to study some problems that were unable to solve using existing codes. The parallel techniques and methods developed in this work can be also applied to other molecular simulation applications.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subjectHigh-performance computing
dc.subjectParallel algorithm
dc.subjectDistributed computing
dc.subjectHeterogenous computing
dc.subjectQuantum chemistry
dc.subjectStokesian dynamics
dc.subjectBrownian dynamics
dc.titleHigh-performance algorithms and software for large-scale molecular simulation
dc.typeDissertation
dc.description.degreePh.D.
dc.contributor.departmentComputational Science and Engineering
thesis.degree.levelDoctoral
dc.contributor.committeeMemberBader, David A.
dc.contributor.committeeMemberVuduc, Richard
dc.contributor.committeeMemberSkolnick, Jeffrey
dc.contributor.committeeMemberSherrill, C. David
dc.date.updated2015-06-08T18:20:22Z


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