In this paper, a generalized Allen-Cahn-type phase-field crystal model with face-centered-cubic ordering structure is presented. By introducing a space-time dependent Lagrange multiplier, the mass conservation is enfo...
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In this paper, a generalized Allen-Cahn-type phase-field crystal model with face-centered-cubic ordering structure is presented. By introducing a space-time dependent Lagrange multiplier, the mass conservation is enforced and the local effect can be reflected. Moreover, the proposed model is lower-order in space and will be more efficient for numerical computation. For the simulation of crystallization, the main challenge is to design practical and stable algorithm which meanwhile guarantees the high-order accuracy. To resolve this problem, we propose a temporally high-order (up to third-order) accurate and linear multi-stage scheme based on implicit-explicit Runge-Kutta approach. The nonlinear term is explicitly treated and the appropriate stabilizer is added to balance the stiffness. By utilizing the Fourier spectral method in space, the numerical calculation is easy to implement. We analytically proved the discrete mass conservation property based on the fully discrete scheme. Extensive numerical experiments are performed to validate the accuracy, efficiency, and capability for phase transition. The effects of parameters and local interaction are investigated in detail. To facilitate the interested readers, we provide MATLAB codes of our proposed method in Appendix A.(c) 2023 Elsevier B.V. All rights reserved.
The Out-of-Distribution (OOD) issue presents a considerable obstacle in offline reinforcement learning. Although current approaches strive to conservatively estimate the Q-values of OOD actions, their excessive conser...
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ISBN:
(纸本)9789819984343;9789819984350
The Out-of-Distribution (OOD) issue presents a considerable obstacle in offline reinforcement learning. Although current approaches strive to conservatively estimate the Q-values of OOD actions, their excessive conservatism under constant constraints may adversely affect model learning throughout the policy learning procedure. Moreover, the diverse task distributions across various environments and behaviors call for tailored solutions. To tackle these challenges, we propose the Adaptable conservative Q-Learning (ACQ) method, which capitalizes on the Q-value's distribution for each fixed dataset to devise a highly generalizable metric that strikes a balance between the conservative constraint and the training objective. Experimental outcomes reveal that ACQ not only holds its own against a variety of offline RL algorithms but also significantly improves the performance of CQL on most D4RL MuJoCo locomotion tasks in terms of normalized return.
We address question of synchronisation in parallel discrete event simulation (PDES) algorithms. We study synchronisation in conservative PDES model adding long-range connections between processing elements. We investi...
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ISBN:
(纸本)9783319629322;9783319629315
We address question of synchronisation in parallel discrete event simulation (PDES) algorithms. We study synchronisation in conservative PDES model adding long-range connections between processing elements. We investigate how fraction of the random long-range connections in the synchronisation scheme influences the simulation time profile of PDES. We found that small fraction of random distant connections enhance synchronisation, namely, the width of the local virtual times remains constant with increasing number of processing elements. At the same time the conservative algorithm of PDES on small-world networks remains free from deadlocks. We compare our results with the case-study simulations.
We simulate model for evolution of local virtual time profile in conservative parallel discrete event the simulation (PDES) algorithm with long-range communication links. The main findings of simulation are that i) gr...
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We simulate model for evolution of local virtual time profile in conservative parallel discrete event the simulation (PDES) algorithm with long-range communication links. The main findings of simulation are that i) growth exponent depends logarithmically on the concentration p of long-range links;ii) utilisation of processing elements time decreases slowly with p. Thismeans that the conservative PDES with long-range communication links is fully scalable.
Considering the coupled nonlinear Schr¨odinger system with multiply components, we provide a novel framework for constructing energy-preserving algorithms. In detail, based on the high order compact finite differ...
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Considering the coupled nonlinear Schr¨odinger system with multiply components, we provide a novel framework for constructing energy-preserving algorithms. In detail, based on the high order compact finite difference method, Fourier pseudospectral method and wavelet collocation method for spatial discretizations, a series of high accurate conservative algorithms are presented. The proposed algorithms can preserve the corresponding discrete charge and energy conservation laws exactly, which would guarantee their numerical stabilities during long time ***, several analogous multi-symplectic algorithms are constructed as comparison. Numerical experiments for the unstable plane waves will show the advantages of the proposed algorithms over long time and verify the theoretical analysis.
Considering the coupled nonlinear Schr?dinger system with multiply components, we provide a novel framework for constructing energy-preserving algorithms. In detail, based on the high order compact finite difference m...
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Considering the coupled nonlinear Schr?dinger system with multiply components, we provide a novel framework for constructing energy-preserving algorithms. In detail, based on the high order compact finite difference method, Fourier pseudospectral method and wavelet collocation method for spatial discretizations, a series of high accurate conservative algorithms are presented. The proposed algorithms can preserve the corresponding discrete charge and energy conservation laws exactly, which would guarantee their numerical stabilities during long time computations. Furthermore, several analogous multi-symplectic algorithms are constructed as comparison. Numerical experiments for the unstable plane waves will show the advantages of the proposed algorithms over long time and verify the theoretical analysis.
Parallel simulation of digital logic circuits is a classic problem of parallel computing by featuring irregular,finegrained *** the context of simulating digital IC design,the granularity of Logic Process(LP),which is...
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ISBN:
(纸本)9781467349994
Parallel simulation of digital logic circuits is a classic problem of parallel computing by featuring irregular,finegrained *** the context of simulating digital IC design,the granularity of Logic Process(LP),which is the basic unit of parallel execution,is generally too small when compared to the scheduling and synchronization overhead of multi-core *** addition,the irregular communication pattern among different LPs makes it difficult to predict and optimize the inter-processor communication *** propose a LP merging algorithm to address the above *** proposed algorithm coarsens the internal structure of input circuits to minimize communication and other *** the same time,our algorithm preserves the inherent concurrency of the *** elaborate the unique set of constraint for LP merging and the corresponding *** on realworld IP cores show that our LP merging algorithm results in a 20% reduction in the number of communication channels,the overall performance is boosted by 30% and the concurrency is maintained at a sufficient level.
Parallel simulation of digital logic circuits is a classic problem of parallel computing by featuring irregular, fine-grained parallelism. In the context of simulating digital IC design, the granularity of Logic Proce...
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ISBN:
(纸本)9781467350006
Parallel simulation of digital logic circuits is a classic problem of parallel computing by featuring irregular, fine-grained parallelism. In the context of simulating digital IC design, the granularity of Logic Process (LP), which is the basic unit of parallel execution, is generally too small when compared to the scheduling and synchronization overhead of multi-core processors. In addition, the irregular communication pattern among different LPs makes it difficult to predict and optimize the inter-processor communication traffic. We propose a LP merging algorithm to address the above problems. The proposed algorithm coarsens the internal structure of input circuits to minimize communication and other overhead. At the same time, our algorithm preserves the inherent concurrency of the simulation. We elaborate the unique set of constraint for LP merging and the corresponding solutions. Experiments on real-world IP cores show that our LP merging algorithm results in a 20% reduction in the number of communication channels, the overall performance is boosted by 30% and the concurrency is maintained at a sufficient level.
Chimera grids method has broad applications in complex flow field simulations because of its convenience of the arbitrary boundary interfaces and the easiness of gird generations of subzones. However, the main disadva...
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ISBN:
(纸本)9781424455690
Chimera grids method has broad applications in complex flow field simulations because of its convenience of the arbitrary boundary interfaces and the easiness of gird generations of subzones. However, the main disadvantage or challenging difficulty lies in the global conservative information exchange between different zones or components. This work aims at assessing of the conservation and effects of the mass flux based interpolation (MFBI) in chimera multi-grid flow solvers where Renolds-Averaged Navier-Stokes (RANS) equations and different turbulence models are introduced to calculate the viscous flows over several high-lift systems. A numerical result reveal that, compared to the direct interpolation scheme, the performance of global conservation of MFBI is much better and also guarantees the coincidence with wind-tunnel experiments.
A novel approach that integrates occlusion culling within the view-dependent rendering framework is proposed. The algorithm uses the prioritized-layered projection（PLP） algorithm to occlude those obscured objects, a...
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A novel approach that integrates occlusion culling within the view-dependent rendering framework is proposed. The algorithm uses the prioritized-layered projection（PLP） algorithm to occlude those obscured objects, and uses an approximate visibility technique to accurately and efficiently determine which objects will be visible in the coming future and prefetch those objects from disk before they are rendered, view-dependent rendering technique provides the ability to change level of detail over the surface seamlessly and smoothly in real-time according to cell solidity value.
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