This paper studies the speedup for multi-level parallel computing. Two models of parallel speedup are considered, namely, fixed-size speedup and fixed-time speedup. Based on these two models, we start with the speedup...
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ISBN:
(纸本)9780769546766
This paper studies the speedup for multi-level parallel computing. Two models of parallel speedup are considered, namely, fixed-size speedup and fixed-time speedup. Based on these two models, we start with the speedup formulation that takes into account uneven allocation and communication latency, and gives an accurate estimation. Next, we propose a high-level abstract case with providing a global view of possible performance enhancement, namely E-Amdahl's Law for fixed-size speedup and E-Gustafson's Law for fixed-time speedup. These two laws demonstrate seemingly opposing views about the speedup of multi-level parallel computing. Our study illustrates that they are not contradictory but unified and complementary. The results lead to a better understanding in the performance and scalability of multi-level parallel computing. The experimental results show that E-Amdahl's Law can be applied as a prediction model as well as a guide for the performance optimization in multi-level parallel computing.
Evaluation of the spin lifetime in thin Silicon films is a challenge because of the necessity of performing appropriate averaging of the strongly scattering momenta depending spin relaxation rates. Here we discuss a t...
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ISBN:
(纸本)9781538648117
Evaluation of the spin lifetime in thin Silicon films is a challenge because of the necessity of performing appropriate averaging of the strongly scattering momenta depending spin relaxation rates. Here we discuss a two-level highly parallelized algorithm to calculate the spin lifetime. This algorithm is based on a hybrid parallelization approach, using the message passing interface MPI as well as OpenMP. Most efficient way to maximally utilize the computational resources is described. Finally, how an application of shear strain can dramatically increase the spin lifetime is shown.
The Natural Laminar Flow (NLF) airfoil/wing design optimization is an efficient method which can reduce significantly turbulence skin friction by delaying transition location at high Reynolds numbers. However, the red...
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The Natural Laminar Flow (NLF) airfoil/wing design optimization is an efficient method which can reduce significantly turbulence skin friction by delaying transition location at high Reynolds numbers. However, the reduction of the friction drag is competitively balanced with the increase of shock wave induced drag in transonic regime. In this paper, a distributed Nash Evolutionary Algorithms (EAs) is presented and extended to multi-level parallel computing, namely multi-levelparallel Nash EAs. The proposed improved methodology is used to solve NLF airfoil shape design optimization problem. It turns out that the optimization method developed in this paper can easily capture a Nash Equilibrium (NE) between transition delaying and wave drag increasing. Results of numerical experiments demonstrate that both wave drag and friction drag performances of a NE are greatly improved. Moreover, performance of the NE is equivalent to that of cooperative Paretooptimum solutions, but it is more efficient in terms of CPU time. The successful application validates efficiency of algorithms in solving complex aerodynamic optimization problem. (C) 2017 Elsevier Inc. All rights reserved.
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