Load-Prediction Scheduling for Computer Simulation of Electrocardiogram on a CPU-GPU PC

Multi-core CPU and GPU technologies upgrades a PC to a personal supercomputer. Many algorithms have been proposed to achieve dynamic scheduling in CPU-GPU hybrid environments. Among them, only pure self-scheduling (PSS) can achieve perfect load balancing in this extremely heterogeneous environment. But PSS can not take full advantage of GPU performance, reduce the overhead of the tail problem, and reduce the dynamic scheduling overhead. In this paper, load-prediction scheduling (LPS) was introduced to solve the above problems. To demonstrate the efficiency of LPS in practical applications, it was implemented to parallelize computer simulation of electrocardiogram. Experimental results of LPS on the computer simulation of electrocardiogram (ECG) show that the LPS algorithm is more efficient than PSS.