Phylogenetic analysis has achieved extraordinary results in domains like species delimitation and evolutionary biology. An essential element behind this success has been the introduction of high performance computing techniques in the step of estimating the phylogenetic likelihoods. This paper describes the design and implementation of a distributed and CPU-GPU based heterogeneous computing system on parallelizing the analysis. The parallelization has been implemented in the state-of-the-art version of MrBayes, a widespread phylogeny reconstruction program. We benchmarked the method and another two GPU-based methods by using 8 distributed computing nodes on Tianhe-1A. The experimental results indicate that the proposed method outstrips BEAGLE and the nMC(3) method by speedup factors of up to 1.98x and 1.68x, respectively. In comparison to the serially implemented MrBayes, a peak speedup of 188x is finally achieved by using 8 Tesla M 2050 GPUs. The proposed method is publicly available to facilitate further research on phylogenetic analysis.