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High Performance Algorithms and Implementations Using Sparse and Parallelization Techniques on MBS

机译:MBS上使用稀疏和并行化技术的高性能算法和实现

摘要

In this paper we will see how the efficiency of the MBS simulations can be improved in two different ways, by considering both an explicit and implicit semi-recursive formulation. The explicit method is based on a double velocity transformation that involves the solution of a redundant but compatible system of equations. The high computational cost of this operation has been drastically reduced by taking into account the sparsity pattern of the system. Regarding this, the goal of this method is the introduction of MA48, a high performance mathematical library provided by Harwell Subroutine Library. The second method proposed in this paper has the particularity that, depending on the case, between 70 and 85% of the computation time is devoted to the evaluation of forces derivatives with respect to the relative position and velocity vectors. Keeping in mind that evaluating these derivatives can be decomposed into concurrent tasks, the main goal of this paper lies on a successful and straightforward parallel implementation that have led to a substantial improvement with a speedup of 3.2 by keeping all the cores busy in a quad-core processor and distributing the workload between them, achieving on this way a huge time reduction by doing an ideal CPU usage
机译:在本文中,我们将了解如何通过考虑显式和隐式半递归公式,以两种不同的方式提高MBS仿真的效率。显式方法基于双速度变换,该双速度变换涉及冗余但兼容的方程组的求解。考虑到系统的稀疏模式,已大大降低了此操作的高计算成本。对此,该方法的目标是引入由Harwell子例程库提供的高性能数学库MA48。本文提出的第二种方法的特殊性在于,根据情况,在70%到85%的计算时间之间,用于评估相对位置和速度矢量的力导数。请记住,评估这些派生类可以分解为并发任务,本文的主要目标在于成功且直接的并行实现,该实现通过将所有内核保持在四核状态,从而使3.2的速度大大提高。核心处理器并在它们之间分配工作负载,从而通过理想的CPU使用率来节省大量时间

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