近年来，随着数据获取设备的不断提高，越来越多的高精度大图像出现在医学、遥感、气象、考古等领域中。这些大图像给使用者带来更多细节信息的同时，也给计算机交互式的显示带来巨大的挑战。设计了一个可扩展的并行工作管道，根据所提出的基于预测的数据管理方法，可以使图像显示和数据导入同步并行的进行；然后，我们基于CUDA（compute unified device architecture）架构，设计针对大图像的放大缩小算法，利用GPU快速的对所显示的图片进行放大缩小处理。我们的算法不需要任何预处理操作，对大图像的浏览操作获得很好的实时性和稳定性，大大提高了浏览的效率。

In recent years, since data acquisition equipments have been improved, a growing number of high-precision large images appear in the medical imaging, remote sensing, meteorology, archeology and other fields. These images not only provide users with detailed information, but also bring out tremendous challenge to display them interactively. We designed a scalable parallel pipeline, according to our algorithm based on proposed method of data management. Then, we design the algorithm to zoom the large image based on CUDA(compute unified device architecture) framework interactively. Our algorithm does not require any pre-processing operation, can obtain excellent real-time performance and stability, and improve the efficiency of the browser greatly.