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Biological computations like Electrocardiological modeling and simulation usually require high-performance computing environments. This paper introduces an implementation of parallel computation for computer simulation of Electrocardiograms (ECGs). We realized the parallel computation for computer simulation of ECGs on a CPU-GPU cluster using a hybrid parallel algorithm with the parallel program development tools--MPI, OpenMP, and CUDA. Furthermore, we proposed a load-prediction static scheduling and load-prediction dynamic scheduling to achieve efficient process-level and thread-level scheduling, respectively. Compared with traditional static and dynamic scheduling, our scheduling schemes are more efficient. In our research, we achieved a speedup of 55.1 using four PCs for the computer simulation of ECGs. This study demonstrates that the cluster can provide a cheap and efficient environment for parallel computations in biological modeling and simulation studies.

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