Self-adaptive energy-saving dispatching method in isomorphic cluster system based on dynamic voltage regulation technology

Abstract

The invention discloses a self-adaptive energy-saving dispatching method in an isomorphic cluster system based on a dynamic voltage regulation technology. The self-adaptive energy-saving dispatching method comprises the following specific steps of: reading a parallel task directed acyclic graph (DAG) file; acquiring an initial task dispatching sequence; acquiring an optimal threshold; dynamically acquiring an optimal threshold according to the parallel task, the system environment and the user performance demand; grouping the tasks: controlling the replication of the tasks by using the optimal threshold, i.e., selectively replicating an optimal precursor of the tasks to balance the performances and energy consumption of the system to acquire an approximate optimal grouping; mapping the tasks: dispatching various groups to a processor which is not occupied; and regulating the voltage of the processor: dynamically adjusting the voltage of the processor by using the idle time of the tasks so as to reduce energy consumption of the processor. According to the self-adaptive energy-saving dispatching method disclosed by the invention, the requirements on the performances and energy consumption of the system are comprehensively considered and the optimal threshold of the system can adapt to the parallel task and the system environment; and the task replication is controlled by using the optimal threshold to acquire the approximate optimal grouping, so that a final dispatching result ensures that the energy consumption is reduced as much as possible on the premise of meeting the requirements of the system.

Description

technical field [0001] The invention relates to a computer system energy-saving scheduling method, in particular to an adaptive energy-saving scheduling method based on dynamic voltage adjustment technology in a homogeneous cluster system. Background technique [0002] A cluster is a parallel distributed processing system consisting of many independent computers connected together, working together like a single integrated computing resource, and it looks like an independent computing system to users. Since the 1990s, with the significant improvement of PC performance and decreasing prices, the development of high-speed networks, and the maturity of cluster software, cluster systems have become the mainstream platform for high-performance computing. Intensive tasks provide a variety of computing needs. [0003] Cluster systems have been widely used in many fields such as industry and commerce. However, cluster systems also consume huge energy while providing powerful compu...

AI Technical Summary

Problems solved by technology

The deficiencies are as follows: ① Some methods only consider performance and completely ignore energy consumption; ② Some energy-saving scheduling methods based on task replication use thresholds to control task replication, but the given thresholds are randomly set and cannot be based on Adaptive adjustment of parallel tasks and system environment leads to unstable scheduling results; ③Although some methods consider both performance and processor energy consumption, they ignore network communication energy consumption

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