Test case prioritization is a type of technique that aims at searching for the test case execution sequence to find faults early based on the whole test case suite. This technique is flexible and barely can miss important test cases, which contributes much benefit to regression testing. Multi-objective test case prioritization, where evolutionary algorithms have been widely used, aims to find a test case execution sequence that suits multiple test criteria. However, the drawback of large computation cost of the algorithms can greatly reduce the value of industrial application. This article proposes a CPU+GPU heterogeneous Computing orientation based multi-objective test case prioritization technique that utilizes advanced general purpose graphic process unit(GPGPU) technique to accelerate the process of test case prioritization. In experiment based on parallel structure, the sequential based parallel fitness and crossover operation computation is designed on NSGA-II and at last achieves 30 times speed-up rate on a well-known industrial open source project. Based on the systematic study on the benefit of different types of parallel strategies, a CPU+GPU heterogeneous computing framework is proposed and a prototype of tools is developed and available online.