Matlab has a high performance at engineering calculation.C# is good at interface development.Combining their advantages together,hybrid programming with Matlab and C # will help to improve the reliability analysis sof...Matlab has a high performance at engineering calculation.C# is good at interface development.Combining their advantages together,hybrid programming with Matlab and C # will help to improve the reliability analysis software efficiency and accuracy significantly.Procedures of hybrid programming with Matlab and C# in reliability analysis software are introduced in this paper.Finally a mathematical problem is tested to verify the feasibility of this programming method.展开更多
Usually simulations on environment flood issues will face the scalability problem of large scale parallel computing.The plain parallel technique based on pure MPI is difficult to have a good scalability due to the lar...Usually simulations on environment flood issues will face the scalability problem of large scale parallel computing.The plain parallel technique based on pure MPI is difficult to have a good scalability due to the large number of domain partitioning.Therefore,the hybrid programming using MPI and OpenMP is introduced to deal with the issue of scalability.This kind of parallel technique can give a full play to the strengths of MPI and OpenMP.During the parallel computing,OpenMP is employed by its efficient fine grain parallel computing and MPI is used to perform the coarse grain parallel domain partitioning for data communications.Through the tests,the hybrid MPI/OpenMP parallel programming was used to renovate the finite element solvers in the BIEF library of Telemac.It was found that the hybrid programming is able to provide helps for Telemac to deal with the scalability issue.展开更多
The purpose of this paper is to develop an implementable strategy of brake energy recovery for a parallel hydraulic hybrid bus. Based on brake process analysis, a dynamic programming algorithm of brake energy recovery...The purpose of this paper is to develop an implementable strategy of brake energy recovery for a parallel hydraulic hybrid bus. Based on brake process analysis, a dynamic programming algorithm of brake energy recovery is established. And then an implementable strategy of brake energy recovery is proposed by the constraint variable trajectories analysis of the dynamic programming algorithm in the typical urban bus cycle. The simulation results indicate the brake energy recovery efficiency of the accumulator can reach 60% in the dynamic programming algorithm. And the hydraulic hybrid system can output braking torque as much as possible.Moreover, the accumulator has almost equal efficiency of brake energy recovery between the implementable strategy and the dynamic programming algorithm. Therefore, the implementable strategy is very effective in improving the efficiency of brake energy recovery.The road tests show the fuel economy of the hydraulic hybrid bus improves by 22.6% compared with the conventional bus.展开更多
In this paper,stochastic global optimization algorithms,specifically,genetic algorithm and simulated annealing are used for the problem of calibrating the dynamic option pricing model under stochastic volatility to ma...In this paper,stochastic global optimization algorithms,specifically,genetic algorithm and simulated annealing are used for the problem of calibrating the dynamic option pricing model under stochastic volatility to market prices by adopting a hybrid programming approach.The performance of this dynamic option pricing model under the obtained optimal parameters is also discussed.To enhance the model throughput and reduce latency,a heterogeneous hybrid programming approach on GPU was adopted which emphasized a data-parallel implementation of the dynamic option pricing model on a GPU-based system.Kernel offloading to the GPU of the compute-intensive segments of the pricing algorithms was done in OpenCL.The GPU approach was found to significantly reduce latency by an optimum of 541 times faster than a parallel implementation approach on the CPU,reducing the computation time from 46.24 minutes to 5.12 seconds.展开更多
文摘Matlab has a high performance at engineering calculation.C# is good at interface development.Combining their advantages together,hybrid programming with Matlab and C # will help to improve the reliability analysis software efficiency and accuracy significantly.Procedures of hybrid programming with Matlab and C# in reliability analysis software are introduced in this paper.Finally a mathematical problem is tested to verify the feasibility of this programming method.
文摘Usually simulations on environment flood issues will face the scalability problem of large scale parallel computing.The plain parallel technique based on pure MPI is difficult to have a good scalability due to the large number of domain partitioning.Therefore,the hybrid programming using MPI and OpenMP is introduced to deal with the issue of scalability.This kind of parallel technique can give a full play to the strengths of MPI and OpenMP.During the parallel computing,OpenMP is employed by its efficient fine grain parallel computing and MPI is used to perform the coarse grain parallel domain partitioning for data communications.Through the tests,the hybrid MPI/OpenMP parallel programming was used to renovate the finite element solvers in the BIEF library of Telemac.It was found that the hybrid programming is able to provide helps for Telemac to deal with the scalability issue.
基金supported by Shanghai Science and Technology Committee(No.0904H155100)
文摘The purpose of this paper is to develop an implementable strategy of brake energy recovery for a parallel hydraulic hybrid bus. Based on brake process analysis, a dynamic programming algorithm of brake energy recovery is established. And then an implementable strategy of brake energy recovery is proposed by the constraint variable trajectories analysis of the dynamic programming algorithm in the typical urban bus cycle. The simulation results indicate the brake energy recovery efficiency of the accumulator can reach 60% in the dynamic programming algorithm. And the hydraulic hybrid system can output braking torque as much as possible.Moreover, the accumulator has almost equal efficiency of brake energy recovery between the implementable strategy and the dynamic programming algorithm. Therefore, the implementable strategy is very effective in improving the efficiency of brake energy recovery.The road tests show the fuel economy of the hydraulic hybrid bus improves by 22.6% compared with the conventional bus.
文摘In this paper,stochastic global optimization algorithms,specifically,genetic algorithm and simulated annealing are used for the problem of calibrating the dynamic option pricing model under stochastic volatility to market prices by adopting a hybrid programming approach.The performance of this dynamic option pricing model under the obtained optimal parameters is also discussed.To enhance the model throughput and reduce latency,a heterogeneous hybrid programming approach on GPU was adopted which emphasized a data-parallel implementation of the dynamic option pricing model on a GPU-based system.Kernel offloading to the GPU of the compute-intensive segments of the pricing algorithms was done in OpenCL.The GPU approach was found to significantly reduce latency by an optimum of 541 times faster than a parallel implementation approach on the CPU,reducing the computation time from 46.24 minutes to 5.12 seconds.
