Task Scheduling Strategy of CPU-GPU Heterogeneous Computing Platform Based on Load Balancing

In central processing unit-graphics processing unit (CPU-GPU) heterogeneous system, the uneven performance of the CPU and GPU caused the system performance to decrease. A hybrid scheduling strategy based on queues was proposed to solve the problem. The computing power of the CPU and GPU was detected to process specified tasks, and computing tasks were allocated to the CPU and GPU according to the perception ratio. The tasks were stored in a bidirectional queue to reduce the additional overhead brought by scheduling. Results show that the system performance of the benchmark test program is improved by using this strategy by an average of 28.07%. Overall, the scheduling strategy can reduce the waiting time after the CPU and GPU complete their respective computing tasks, balance the load between the system CPU and GPU, and improve the system performance.