Laplace transform method has proved to be very efficient and easy to parallelize for the solution of time-dependent problems. However, the synchronization delay among processors implies an upper bound on the expectable acceleration factor, which leads to a lot of wasted time. In this paper, we propose an original asynchronous Laplace transform method formalized for quasilinear problems based on the well-known Gaver–Stehfest algorithm. Parallel experiments show the convergence of our new method, as well as several interesting properties compared with the classical algorithms.

中文翻译：

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基于拉普拉斯变换的异步时间并行方法

拉普拉斯变换方法已被​​证明是非常有效且易于并行化以解决时间相关问题的方法。然而，处理器之间的同步延迟意味着可预期加速因子的上限，这会导致大量时间浪费。在本文中，我们提出了一种原始的异步拉普拉斯变换方法，该方法基于著名的 Gaver-Stehfest 算法针对拟线性问题进行形式化。并行实验显示了我们的新方法的收敛性，以及与经典算法相比的几个有趣的特性。