@article {Simula.simula.2096,
	title = {High Efficient Sedimentary Basin Simulations on Hybrid CPU-GPU Clusters},
	journal = {Cluster Computing},
	volume = {17},
	number = {2},
	year = {2014},
	pages = {359-369},
	publisher = { },
	doi = {10.1007/s10586-013-0300-9},
	author = {Wen, Mei and Su, Huayou and Wei, Wenjie and Wu, Nan and Cai, Xing and Zhang, Chunyuan}
}
@article {Simula.simula.2602,
	title = {Performance Modeling of Serial and Parallel Implementations of the Fractional Adams-Bashforth-Moulton Method},
	journal = {Fractional Calculus and Applied Analysis},
	volume = {17},
	number = {3},
	year = {2014},
	pages = {617-637},
	publisher = { },
	author = {Zhang, Wei and Wei, Wenjie and Cai, Xing}
}
@article {Simula.simula.1490,
	title = {Balancing Efficiency and Accuracy for Sediment Transport Simulations},
	journal = {Computational Science \& Discovery},
	volume = {6},
	number = {1},
	year = {2013},
	pages = {015011},
	abstract = {Simulating multi-lithology sediment transport requires numerically solving a fully-coupled system of nonlinear partial differential equations. The most standard approach is to simultaneously update all the unknown fields at each time step. Such a fully-implicit strategy is computationally demanding due to the need of Newton-Raphson iterations, each having to set up and solve a large system of linearized algebraic equations. Fully-explicit numerical schemes that do not solve linear systems are possible to devise, but suffer from lower numerical stability and accuracy. If we count the total number of floating-point operations needed to achieve stable numerical solutions with a prescribed level of accuracy, the fully-implicit approach probably wins over its fully-explicit counterpart. However, the latter may nevertheless win in the overall computation time, because computers achieve higher hardware efficiency for simpler numerical computations. Adding to this competition, there are semi-implicit numerical schemes that lie between the two extremes. This paper has two novel contributions. First, we device a new semi-implicit scheme that has secondorder accuracy in the temporal direction. Second, and more importantly, we propose a simple prediction model for the overall computation time on multicore architectures, applicable to many numerical implementations. Based on performance prediction, appropriate numerical schemes can be chosen by considering accuracy, stability, and computing speed at the same time. Our methodology is tested by numerical experiments modeling the sediment transport in Monterey Bay.},
	doi = {10.1088/1749-4699/6/1/015011},
	author = {Wei, Wenjie and Clark, Stuart and Su, Huayou and Wen, Mei and Cai, Xing}
}
@phdthesis {Simula.simula.1692,
	title = {Effective Use of Multicore-Based Parallel Computers for Scientific Computing},
	year = {2012},
	month = {December},
	school = {University of Oslo},
	type = {phd},
	author = {Wei, Wenjie}
}
@inproceedings {Simula.simula.1342,
	title = {Using 1000+ GPUs and 10000+ CPUs for Sedimentary Basin Simulations},
	journal = {Proceedings of IEEE Cluster 2012},
	year = {2012},
	pages = {27-35},
	publisher = {IEEE},
	type = {Conference},
	address = {Los Alamitos, California  {\textbullet} Washington {\textbullet} Tokyo},
	keywords = {Conference},
	doi = {10.1109/CLUSTER.2012.37},
	author = {Wen, Mei and Su, Huayou and Wei, Wenjie and Wu, Nan and Cai, Xing and Zhang, Chunyuan}
}
@inproceedings {Simula.simula.374,
	title = {An OpenMP-Enabled Parallel Simulator for Particle Transport in Fluid Flows},
	journal = {Proceedings of the International Conference on Computational Science, ICCS 2011},
	volume = {4},
	year = {2011},
	pages = {1475-1484},
	publisher = {Elsevier Science},
	type = {Conference},
	address = { },
	abstract = {By using C/C++ programming and OpenMP parallelization, we implement a newly developed numerical strategy for simulating particle transport in sparsely particle-laden fluid flows. Due to its highly dynamic property of the chosen numerical framework, the implementation needs to properly handle the moving, merging and splitting of a large number of particle lumps. We show that a careful division of the entire computational work into a set of distinctive tasks not only produces a clearly structured code, but also allows taskwise parallelization through appropriate use of OpenMP compiler directives. The performance of the OpenMP-enabled parallel simulator is tested on representative architectures of multicore-based shared memory, by running a large case of particle transport in a pipe flow. Attention is also given to a number of performance-critical features of the simulator.},
	doi = {10.1016/j.procs.2011.04.160},
	author = {Wei, Wenjie and Al-Khayat, Omar and Cai, Xing},
	editor = {Sato, M. and Matsuoka, S.}
}
@article {Simula.sc.792,
	title = {Computational Modeling of the Initiation and Development of Spontaneous Intracellular Ca2+ Waves in Ventricular Myocytes},
	journal = {Philosophical Transactions of the Royal Society A},
	volume = {368},
	number = {1925},
	year = {2010},
	month = {August},
	pages = {3953-3965},
	doi = {10.1098/rsta.2010.0146},
	author = {Li, Pan and Wei, Wenjie and Cai, Xing and Soeller, Christian and Cannell, Mark and Arun V. {Holden}}
}
@inproceedings {Simula.sc.816,
	title = {Numerical Analysis of a Dual-Sediment Transport Model Applied to Lake Okeechobee, Florida},
	journal = {Proceedings of the 2010 Ninth International Symposium on Parallel and Distributed Computing},
	year = {2010},
	pages = {189-194},
	publisher = {IEEE Computer Society Press},
	type = {Conference},
	abstract = {In this work, we study two numerical strategies for solving a coupled system of distinct nonlinear partial differential equations, which can be used to model dual-lithology sedimentation. Using high-resolution bathymetry data of Lake Okeechobee, Florida, we study the stability and computational speed of these numerical strategies. The fully-explicit scheme is straightforward to implement and requires a relatively small amount of computation per time step. However, this simple numerical strategy has to use small time steps to ensure stability. These small time steps may render the explicit solver impractical for long-term and high-resolution basin simulations. As a comparison, we have implemented a semi-implicit scheme, where the two partial differential equations at each time step are solved implicitly in sequence. This semi-implicit scheme is numerically stable even for very large time steps. Using parallel computing, we have applied both schemes to a realistic case, Lake Okeechobee, Florida. The simulation successfully diffused material along a river-channel and into the lake. Both MPI-based implementations demonstrated satisfactory parallel efficiency on a multicore-based cluster.},
	isbn = {978-1-4244-7602-2},
	doi = {10.1109/ISPDC.2010.29},
	author = {Clark, Stuart and Wei, Wenjie and Cai, Xing},
	editor = {Ozturan, Can}
}
@misc {Simula.cg.18,
	title = {OpenMP: an Easy Parallel Approach for Scientific Computing on Multi-Core Architecture},
	howpublished = {A short course respectively given at Simula in March and University of Oslo in May},
	year = {2010},
	month = {May},
	author = {Wei, Wenjie and Cai, Xing}
}
@misc {Simula.simula.294,
	title = {Parallel Programming, OpenMP},
	howpublished = {CBC Lecture on Parallel Programming, OpenMP, March 17},
	year = {2010},
	author = {Wei, Wenjie}
}
@inproceedings {Simula.SC.204,
	title = {Evolution of Intracellular Ca2+ Waves From About 10,000 RyR Clusters: Towards Solving a Computationally Daunting Task},
	journal = {The Fifth International Conference on Functional Imaging and Modeling of the Heart},
	year = {2009},
	pages = {11-20},
	publisher = {Springer},
	type = {Conference},
	doi = {10.1007/978-3-642-01932-6},
	author = {Li, Pan and Wei, Wenjie and Cai, Xing and Soeller, Christian and Cannell, Mark and Arun V. {Holden}},
	editor = {Ayache, Nicholas and Delingette, Herv{\'e} and Sermesant, Maxime}
}
@misc {Simula.SC.604,
	title = {Parallel Simulation of Dual Lithology Sedimentation},
	year = {2009},
	note = {Second prize winner of the poster competition at the conference.},
	author = {Wei, Wenjie and Clark, Stuart and Cai, Xing and Are Magnus {Bruaset}}
}
