The paper presents a hierarchical approach to the problem of energy-aware task allocation in a distributed HPC system consisting of several computing clusters. The solution involves the control of clusters and the use of network traffic engineering methods to minimize overall energy consumption. The advantages of the hierarchical approach are twofold: first entities controlling parts of computing infrastructure may decide how much of their responsibility is delegated to the coordinator, next the computational complexity of related mathematical programming problems may be reduced, and their solution may be done in parallel. The mathematical programming problem of task allocation is defined in the centralized form first. After discussing its computation complexity and related organizational difficulties, it is decomposed to form a hierarchy. Finally, heuristics for allocation are proposed and verified via numerical simulation.

本文针对由多个计算集群组成的分布式HPC系统中的能量感知任务分配问题提出了一种分层方法。该解决方案涉及群集的控制和网络流量工程方法的使用，以最大程度地降低总体能耗。分层方法的优点是双重的：首先，控制计算基础结构各部分的实体可以决定将其职责的多少委派给协调器，其次可以降低相关数学编程问题的计算复杂度，并且可以并行完成它们的解决方案。 。首先以集中形式定义任务分配的数学编程问题。在讨论了其计算复杂性和相关的组织困难之后，将其分解以形成一个层次结构。最后，