GPU accelerated image processing using Quasar

Today's algorithms (e.g., image/video processing, hyperspectral sensor data, ...) require huge amounts of data. For many algorithms, a good computational performance is indispensable for use in practical applications. These applications are often targeted toward a big diversity of devices, such as desktop PCs, tablets, smartphones, mini PCs. To reach a good computational performance, modern GPUs bring speedups of 10x-200x for highly parallel processing tasks, but one main disadvantage is the difficulty of programming: not only does (properly) programming a GPU require an extensive in-depth knowledge of the details of a GPU, the development efforts are usually high, which causes GPUs not easily to be used for research purposes, e.

Real-time depth estimation and view interpolation using Quasar

In this paper, we first present a new programming framework, Quasar, for high-level programming on heterogeneous CPU and single/multi-GPU systems. Quasar consists of a high-level language, a corresponding integrated development environment (IDE), a …