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Liu, Eric
University of Calgary
Calgary, Canada
 
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Hui Liu works at the University of Calgary, Canada, as a research associate. He holds a PhD degree in Computational Mathematics and Parallel Computing from the Chinese Academy of Sciences (2010), and a BSc degree in Computational Mathematics from the University of Science and Technology of China (USTC, 2005).

In 2005, after fulfilling his bachelor’s degree in computational mathematics, he was accepted for a PhD scholarship at the Academy of Mathematics and Systems Science, Chinese Academy of Sciences, where he studied computational mathematics and parallel computing. During his PhD program, he studied adaptive finite element methods (h-, p-, hp-adaptive methods), parallel computing, dynamic load balancing, encoding and decoding of Hilbert space-filling curves, and algorithm design. He developed encoding and decoding algorithms for arbitrary Hilbert space-filling curves.

In 2010, he joined the Reservoir Simulation Group, University of Calgary, and worked on GPU computing. It is well known that linear solvers occupy most simulation time during black oil simulations, and if linear solvers are accelerated, reservoir simulations can be sped up. He worked on the acceleration of linear solvers and preconditioners using GPUs, including Krylov subspace solvers, algebraic multigrid solvers, and various preconditioners. He implemented two linear solver packages: one for a single GPU and another for multi-GPUs.

In 2013, he started a parallel platform project to support the development of large-scale reservoir simulations. The platform is designed for distributed-memory parallel systems and uses MPI for communications. It provides gridding, load balancing, mapping, parallel linear solvers, preconditioners, well modeling, visualization, keyword parsing, and parallel input and output. The platform has been utilized for black oil models, compositional models, and thermal models. New parallel preconditioners specialized for reservoir simulation have been developed. The platform and parallel reservoir simulators are scalable, and large-scale reservoir models with billions of grid cells can be simulated.

His research interests include numerical methods for partial differential equations, reservoir simulation, linear/nonlinear solvers, algebraic multigrid solvers, preconditioners, parallel computing, and GPU computing. He has had several papers published in the Journal of Computational Mathematics, Journal of Computational Physics, Numerical Linear Algebra with Applications, and Computers & Mathematics with Applications.

 
 
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  Simulating rigid body fracture with surface meshes
Zhu Y., Bridson R., Greif C. ACM Transactions on Graphics (TOG) 34(4): 1-11, 2015.  Type: Article

Simulation of rigid body fracturing has been a hot research topic in computer graphics and applied sciences, such as collision detection and the simulation of explosions. Many methods have been proposed and applied to rigid body fractu...

Feb 16 2016  
  A direct tridiagonal solver based on Givens rotations for GPU architectures
Venetis I., Kouris A., Sobczyk A., Gallopoulos E., Sameh A. Parallel Computing 49(C): 101-116, 2015.  Type: Article

Tridiagonal linear systems arise from discretizations of differential equations. The associated matrices have non-zero elements only on the main diagonal and on the two diagonals directly above and below the main diagonal. In practice,...

Jan 14 2016  
  A computational approach to nonparametric regression: bootstrapping CMARS method
Yazıcı C., Yerlikaya-Özkurt F., Batmaz İ. Machine Learning 101(1-3): 211-230, 2015.  Type: Article

A well-defined model can relate phenomena and conclusions, which can enhance our understanding of knowledge and help our work decisively. In statistics, one popular research topic is to formulate mathematical models using existing data...

Dec 9 2015  
  Performance modeling for hierarchical graph partitioning in heterogeneous multi-core environment
Chan S., Ling T., Aubanel E. Parallel Computing 46(C): 78-97, 2015.  Type: Article

Graph partitioning is an interesting topic in parallel scientific computing that has been studied for decades. For many numerical methods, such as finite element methods (FEMs), finite difference methods, and finite volume methods, a m...

Nov 12 2015  
  Experiments on density-constrained graph clustering
Görke R., Kappes A., Wagner D. Journal of Experimental Algorithmics 191.1-1.31, 2015.  Type: Article

Graph clustering is the task of identifying dense sub-graphs of a given graph such that these sub-graphs are sparsely interconnected. In this paper, the authors conduct an experimental evaluation of greedy graph clustering algorithms. ...

Sep 8 2015  
   Uniformly convergent hybrid schemes for solutions and derivatives in quasilinear singularly perturbed BVPs
Zheng Q., Li X., Gao Y. Applied Numerical Mathematics 91(C): 46-59, 2015.  Type: Article

A singularly perturbed boundary-value problem is a boundary-value problem that contains a small parameter whose value cannot be approximated by setting to zero. The one-dimensional singularly perturbed quasilinear convection-diffusion ...

Jul 27 2015  
   Numerical integration on GPUs for higher order finite elements
Banaś K., Płaszewski P., Macioł P. Computers & Mathematics with Applications 67(6): 1319-1344, 2014.  Type: Article

Finite element methods (FEMs) are numerical methods for finding approximate solutions to partial differential equations. When a problem is presented, a mesh and a finite element space are required to be defined. Regular choices for mes...

Oct 22 2014  
  Surprising computations
Ascher U. Applied Numerical Mathematics 62(10): 1276-1288, 2012.  Type: Article

A computer simulation of differential equations is a computer program applied to solve differential equations using numerical methods, such as the finite difference, finite volume, and finite element methods. Simulators are indispensab...

Dec 18 2012  
  Large-scale parallel Monte Carlo tree search on GPU
Rocki K., Suda R.  IPDPSW 2011 (Proceedings of the 25th IEEE International Parallel and Distributed Processing Symposium, Anchorage, AK, May 16-20, 2011) 2034-2037, 2011.  Type: Proceedings

“Monte Carlo tree search (MCTS) is a method for making optimal decisions in artificial intelligence (AI) problems.” It takes random samples in a given decision space and builds a search tree according to the simulat...

Nov 30 2012  
  Algebraic multigrid solver on clusters of CPUs and GPUs
Neic A., Liebmann M., Haase G., Plank G.  PARA 2010 (Proceedings of the 10th International Conference on Applied Parallel and Scientific Computing, Reykjavík, Iceland, Jun 6-9, 2010) 389-398, 2012.  Type: Proceedings

An algebraic multigrid solver (AMG) is an iterative method for solving symmetric positive definite linear systems arising from elliptic partial differential equations. When solving linear systems, we know that oscillatory errors conver...

Aug 20 2012  
 
 
 
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