A GPU Heterogeneous Cluster Scheduling Model for Preventing Temperature Heat Island

Abstract

Abstract. With the development of GPU general-purpose computing, GPU heterogeneous cluster has become a widely used parallel data processing solution in modern data center. Temperature management and controlling has become a new research hotspot in big data continuous computing. Temperature heat island in cluster has important influence on computing reliability and energy efficiency. In order to prevent the occurrence of GPU cluster temperature heat island, a big data task scheduling model for preventing temperature heat island was proposed. In this model, temperature, reliability and computing performance are taken into account to reduce node performance difference and improve throughput per unit time in cluster. Temperature heat islands caused by slow nodes are prevented by optimizing scheduling. The experimental results show that the proposed scheme can control node temperature and prevent the occurrence of temperature heat island under the premise of guaranteeing computing performance and reliability.