Abstract: A phase space probabilistic clustering algorithm base on multi-scale quantum harmonic oscillator algorithm(PSPCA-MQHOA) is proposed to solve the problem that task scheduling and resource allocation of large clusters. Firstly, the cluster operating status is projected into the phase space, and the complex working state is transformed into the point set in the phase space. Furthermore, the phase space is meshed to form the multi-scale quantum harmonic oscillator algorithm(MQHOA). Finally, probabilistic clustering of cluster nodes is carried out by using the probability interpretation of wave function in the MQHOA process. PSPCA-MQHOA inherits the advantages of the MQHOA algorithm, such as explicit physical model, strong search capabilities, exact results, and PSPCA-MQHOA has few iterations due to the discretized phase space. Experiments show that PSPCA-MQHOA can be applied to a variety of clusters.