Abstract
Ultra-high-resolution visualizations of large-scale data sets are often rendered using a remotely located graphics cluster that does not have a connected display. In such instances, rendered images must either be streamed over a network for live viewing, or saved to disk for later viewing. This process introduces the additional overhead associated with transferring data off of the GPU device. We present early work on real-time compression of rendered visualizations that aims to reduce both the device-to-host data transfer time and the I/O time for streaming or writing to disk. By using OpenGL / CUDA interop, images are compressed on the GPU prior to transferring the data to main memory. Although there is a computation cost to performing compression, our results show that this overhead is more than offset by the reduced data transfer and I/O times.