Task scheduling method and system facing mixed load in heterogeneous cluster

Abstract

The invention relates to a task scheduling method and a task scheduling system facing mixed load in a heterogeneous cluster. The method comprises the following steps: a resource scheduler is used for receivingthe beats of machines and maintaining the cluster attributes of the machines; a job manager is used for receiving and resolving operation to obtain a plurality of tasks; the job manager is used for setting the attribute cluster and restrain demand for the task, and transmitting the task information to a resource manager; the resource scheduler is an optimal machine which is used for meeting the restraint of task matching, and returning a matching relation between the task and the machine to the job manager; and the job manager is used for transmitting the task to an actuator on the matched machine for executing tasks. The attribute and task requirement of the heterogeneous machine can be indicated by an easily expandable description method, and the optimal machine is distributed for the task based on taking the hard constraint as a filtration standard and the soft constraint as a selection standard, therefore the executing efficiency of the task and the integral performance of the system can be obviously improved.

Description

technical field [0001] The invention relates to a mixed load-oriented task scheduling method and system in a heterogeneous cluster, belonging to the field of computer parallel computing. Background technique [0002] In recent years, cluster machines have shown increasingly significant heterogeneity. Modern clusters tend to be large, run for long periods of time, and may even be geographically distributed. Throughout its lifecycle, clusters often need to update machines. In addition, in the cluster integration scenario, the cluster administrator may integrate several small clusters of different batches into one large cluster. Given the above, it is likely that there are some differences in the hardware and software of the cluster. [0003] On the other hand, with the continuous development of cloud computing, it has become a trend to run mixed loads on the same cluster, which has many benefits, such as improving resource utilization, sharing data, and reducing operation a...

AI Technical Summary

Problems solved by technology

However, due to the heterogeneity of tasks and machines, task scheduling must consider various constraints

Existing methods cannot describe a wide variety of constraints, nor can they schedule tasks to the optimal machine according to the constraints, which will lead to abnormal execution of tasks or significantly longer running time, which seriously affects the execution efficiency of tasks and the performance of task scheduling systems. overall performance

Images