Nowadays modern computer GPU (Graphic Processing Unit) became widely used to improve the performance of a computer, which is basically for the GPU graphics calculations, are now used not only for the purposes of calculating the graphics but also for other application. In addition, Graphics Processing Unit (GPU) has high computation and low price. This device can be treat as an array of SIMD processor using CUDA software. This paper talks about GPU application, CUDA memory and efficient CUDA memory using Reduction kernel. High-performance GPU application requires reuse of data inside the streaming multiprocessor (SM). The reason is that onboard global memory is simply not fast enough to meet the needs of all the streaming multiprocessor on the GPU. In addition, CUDA exposes the memory space within the SM and provides configurable caches to give the developer the greatest opportunity of data reuse.