Scheduling and Parallel Computing

考虑一个大型的计算任务，例如，求解一个大型的线性方程组。该任务可以分成许多较小的作业，然后在大量不同的异构计算资源上调度和排队，并并行执行。不同资源（例如cpu和gpu）的处理需求是不同的，它们也可能具有不同的通信成本。在这个项目中，我们将有兴趣在设计（和实现）新的分布式调度算法之前理解随机效应。

Consider a large computational task, for instance, solving a large system of linear equations. This task can be split into many smaller jobs which are then scheduled and queued at a large number of different heterogeneous computing resources and are executed in parallel. The processing requirements of the different resources (for instance CPUs and GPUs) are different, and they may well have different communication costs. In this project we will be interested in understanding the stochastic effects before designing (and implementing) novel distributed scheduling algorithms.