Graphics Processing Units (GPUs) embrace many-core compute devices where massively parallel compute threads are offloaded from CPUs. This heterogeneous nature of GPU computing raises non-trivial data transfer problems especially against latency-critical real-time systems. However even the basic characteristics of data transfers associated with GPU computing are not well studied in the literature. In this paper, the authors investigate and characterize currently-achievable data transfer methods of cutting-edge GPU technology. They implement these methods using open-source software to compare their performance and latency for real-world systems.