Research On Task Allocation And Load Balance For Multi-core Processors

Over the years, processor performance mainly depends on its frequency increased, however, this approach is close to the limit by the chip power consumption, heat and other factors. Under this condition, the multi-core processor came into being and has been developing rapidly, while multi-core processor system provides a broad space for the development of task scheduling and load balancing research. At present, when task scheduling and load balancing takes place on multi-core processors, first, the processes are assigned to the processors, then the nodes belonging to processes are scheduled on processing cores, the goal is to make the overall system execution time at least and maximize to play the multi-core processors advantage. In this paper, the existing task allocation and task scheduling algorithm is improved, furthermore, we take load balancing into account between processors and processing cores. The main work includes the following two aspects:On the one hand, we establish the task groups based on the existing DAG task allocation model and improve the task allocation algorithm, the improved algorithm compounding the processes not olny considers the communication time but foci on the two factors, which is the communication time and execution time. According to the setting standard, the algorithm will choose the best two processes to compound and make the task nodes will be more balanced on the processors. Simulation experiments show that the improved task allocation algorithm is superior to the existing task allocation algorithm in the level of workload and the execution time on the processor.On the other hand, taking the analysis based on the existing genetic algorithm, we propose a balanced population Genetic Algorithm algorithm named BPGA. The BPGA improves the standard genetic algorithm for its generating initial population, which has a certain blindness on the issue, frist, we take the task nodes category under the constraints of the height of task nodes; then, we select task nodes depending on the height of their value and processing cores randomly to make the nodes randomly assigned to processing cores,at the same time,we also making the number of nodes assigned to each processing core is load balancing; finally, we move the task nodes by their execution time on each processing core to make the processing cores relative balance after the nodes have been allocated, which can reduce the overall task execution time to make further balancing load between processing cores and also allow the system to maximize resource utilization. Experimental results show that the BPGA algorithm in the load balancing and the execution time has an advantage over other algorithms.