Title: 86th NIA CFD Seminar “Scalable Parallel Delaunay Image-to-Mesh Conversion for Shared and Distributed Memory Architectures”
Date: Tuesday, April 25, 2017
Time: 11:00am-noon (EST)
Room: NIA, Rm137
Speaker: Daming Feng, PhD Candidate, ODU
Abstract: Scalable, stable and portable parallel Image-to-Mesh (I2M) conversion algorithms with quality and fidelity guarantees are important for the real world bio-engineering and medical applications, such as the image guided therapy, patient-specific interactive surgery simulation and so on. Supercomputers, either shared memory or distributed memory, are more and more popular to be used for high performance computing. However, most current parallel mesh generation algorithms are desktop-based. Such mesh generation algorithms, when run on supercomputers, are either conservative in leveraging available concurrency or depend on the solution of the domain decomposition problem which makes the scalability of these algorithms very limited. In addition, the implementation of parallel mesh generation algorithms on supercomputers brings new challenges because of their special memory architecture. Therefore, implementing an efficient parallel mesh generation algorithm targeting the shared and distributed supercomputers is still an open problem. I will describe several parallel mesh generation algorithms we proposed that are scalable on shared and distributed memory supercomputers. These algorithms will also contribute to the understanding of the challenging characteristics of adaptive and irregular applications on supercomputers consisting of thousands of cores.
Bio: Daming Feng is a PhD candidate in Computer Science Department of Old Dominion University. He works since 2012 as a research assistant in the Center for Real-Time Computing (CRTC) in Old Doninion University, Norfolk, VA. He advised by Dr. Nikos Chrisochoides and Dr. Andrey Chernikov. His current research focuses on quality and fidelity guaranteed mesh generation and high scalable parallel mesh generation for shared and distributed memory architectures. His other research interests mesh visualization, hybrid programming and high performance computing. Especially, he is interested in applying the integration of mesh generation and hybrid programming techniques to analyze and solve the challenging real word applications such as interactive surgery simulation and gene model expression. He published more than 10 papers and some of them are published on the journals with high cited rate such as Parallel Computing and Computer-Aided Design. He earned his B.S. in Computer Science Department from Harbin University of Science of Technology and M.S. in Computer Science Department from Soochow University in China.