Benchmarking multi-GPU applications on modern multi-GPU integrated systems

GPUs are very powerful computing accelerators that are often employed in single-device configuration. However, there is a steadily growing interest in using multiple GPUs in a concurrent way both to overcome the memory limitations of the single device and to further reduce execution times. Until recently, communication among GPUs had been carried out mainly by using networking technologies originally devised for standard CPUs with the CPU playing an active role in the communication. However, new alternatives start to be available in which a moderate number of GPUs are directly connected each other by means of proprietary technologies. We present the results of a set of experiments aimed at assessing the performance of some of these hardware/software platforms using a particularly challenging application as a benchmark. We release its source code to facilitate people interested in reproducing or extending our results.