Research And Application Of Computing Model Based On CPU-GPU Heterogeneous Platform

With the rapid development of the graphics processor unit(GPU) performance recent years, in the related fields of parallel computing, especially in large-scale scientific computing GPU play an extremely important role, using CPU-GPU to accelerate the large-scale scientific computing has become an inevitable trend in the development of future high-performance computing, so CPU-GPU-based parallel computing model has increasingly become a hot area of domestic and foreign high-performance computing research, there has made a number of CPU-GPU-based parallel computing models, but most are very simple in computing model, and they could not make full use of the performance of the CPU and GPU.This paper based on the inherent characteristics of the CPU and GPU parallel computing and their respective advantages, we propose a CPU-GPU-based computational model, which design a task scheduling mechanism, makes the CPU and GPU can participate in the computing of task at the same time, and gives a coordination strategy, making the data could be dynamic division in the CPU and GPU to achieve load balancing of the processors, compared with the traditional model, this model could make use of existing resources more efficiently, the model also presents a data classification method for massive task, solute the problem that the GPU could not accommodate all the data at one time, the scheduling mechanism and division method of the model is suitable for many typical applications, such as matrix operations, image processing, text processing and many other massive parallel computing, and designed a interface model for users and implement the interfaces for users, the interface make users to achieve their parallel needs easily and effectively.Optimization of GPU programming is one core of the GPU general computing, so on the basis of this computing model this paper realized three typical applications, analysis and combined with the characteristics of application algorithms and design effective parallel algorithm, which using a variety of parallel optimization programming, test results show that the optimal strategies given by the model and use of the optimization programming methods is feasible and effective.