利用OpenMP并行计算加速基于粒子群算法的NURBS刀具路径进给速度优化

Rafał Szczepański, Krystian Erwiński, M. Paprocki
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引用次数: 4

摘要

在过去的几年里,数控机床的时间最优进给曲线的生成受到了极大的关注。这是一个复杂的优化问题,通常需要很长的计算时间。在该方案中,采用基于增广拉格朗日约束处理技术的并行粒子群优化算法进行优化。为了减少计算时间,采用Open Multi-processing重新实现了作者先前开发的算法。OpenMP利用现代cpu运行多线程的能力,并通过并行处理减少算法的运行时间。对算法在多核系统上并行化后的性能增益(加速)进行了测试。通过一个刀具轨迹实例生成的时间最优进给曲线的实验结果,说明了并行计算提高算法性能的能力。
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Accelerating PSO based feedrate optimization for NURBS toolpaths using parallel computation with OpenMP
Over the last few years generation of a time-optimal feedrate profile for CNC machines has recieved significant attention. This is a difficult optimization problem usually requiring long computation time. In the proposed solution, optimization is performed by parallel Particle Swarm Optimization with Augmented Lagrangian constraint handling technique. In order to decrease computation time the authors previously developed algorithm was reimplemented using Open Multi-processing. OpenMP utilizes the ability of modern CPUS to run multiple threads and reduce the algorithm's runtime by using parallel processing. The performance gain (speed-up) of the algorithm parallelized on a multi-core system has been tested. The experimental results of a time-optimal feedrate profile generated using an example toolpath are presented to illustrate the capabilities of parallel computation to improve the algorithm's performance.
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