Efficient parallel processing by improved CPU-GPU interaction

In this digital world, more than 90% of desktop and notebook computers have integrated Graphics Processing Units i.e. GPU´s, for better graphics processing. Graphics Processing Unit is not only for graphics applications, even for non-graphics applications too. In the past few years, the graphics programmable processor has evolved into an increasingly convincing computational resource. But GPU sits idle if graphics job queue is empty, which decreases the GPU´s efficiency. This paper focuses on various tact to overcome this problem and to make the CPU-GPU processing more powerful and efficient. The graphics programmable processor or Graphics processing unit is especially well suited to address problem sets expressed as data parallel computation with the same program executed on many data elements concurrently. The objective of this paper is to increase the capabilities and flexibility of recent GPU hardware combined with high level GPU programming languages: to accelerate the building of images in a frame buffer intended for output to a display, and, to provide tremendous acceleration for numerically intensive scientific applications. This paper also gives some light on major applicative areas where GPU is in use and where GPU can be used in future.