0000000000733287

AUTHOR

Gerrit Voss

showing 2 related works from this author

Real-time simulation of tissue deformation for the nasal endoscopy simulator (NES).

1999

Endonasal sinus surgery requires a great amount of training before it can be adequately performed. The complicated anatomy involved, the proximity of relevant structures, and the variability of the anatomy due to inborn or iatrogenic variations make several complications possible. Today, cadaver dissections are the "gold standard" for surgical training. To overcome the drawbacks of traditional training methods, the Fraunhofer Institute for Computer Graphics is currently developing a highly interactive medical simulation system for nasal endoscopy and endonasal sinus surgery, in cooperation with the Mainz University Hospital. For the simulation of a rhinoscopic procedure, not only are the re…

3D interactionmedicine.medical_specialtyFinite Element AnalysisNoseComputer graphicsUser-Computer InterfaceReal-time simulationCadaverParanasal SinusesCadaverComputer GraphicsMedicineHumansComputer SimulationSimulationEndoscopesTissue deformationNasal endoscopybusiness.industryMedical simulationDissectionEndoscopyUniversity hospitalSurgical InstrumentsComputer Science ApplicationsGeneral SurgerySurgeryClinical CompetencebusinessFamily PracticeComputer aided surgery : official journal of the International Society for Computer Aided Surgery
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Mapping of BLASTP Algorithm onto GPU Clusters

2011

Searching protein sequence database is a fundamental and often repeated task in computational biology and bioinformatics. However, the high computational cost and long runtime of many database scanning algorithms on sequential architectures heavily restrict their applications for large-scale protein databases, such as GenBank. The continuing exponential growth of sequence databases and the high rate of newly generated queries further deteriorate the situation and establish a strong requirement for time-efficient scalable database searching algorithms. In this paper, we demonstrate how GPU clusters, powered by the Compute Unified Device Architecture (CUDA), OpenMP, and MPI parallel programmi…

Source codeSequence databaseComputer sciencemedia_common.quotation_subjectMessage passingParallel computingGPU clusterComputational scienceCUDATask (computing)Search algorithmGenBankScalabilityAlgorithmmedia_common2011 IEEE 17th International Conference on Parallel and Distributed Systems
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