2017 IEEE Real-Time Systems Symposium (RTSS) (2017)
Dec 5, 2017 to Dec 8, 2017
The push towards fielding autonomous-driving capabilities in vehicles is happening at breakneck speed. Semi-autonomous features are becoming increasingly common, and fully autonomous vehicles are optimistically forecast to be widely available in just a few years. Today, graphics processing units (GPUs) are seen as a key technology in this push towards greater autonomy. However, realizing full autonomy in mass-production vehicles will necessitate the use of stringent certification processes. Currently available GPUs pose challenges in this regard, as they tend to be closed-source “black boxes” that have features that are not publicly disclosed. For certification to be tenable, such features must be documented. This paper reports on such a documentation effort. This effort was directed at the NVIDIA TX2, which is one of the most prominent GPU-enabled platforms marketed today for autonomous systems. In this paper, important aspects of the TX2's GPU scheduler are revealed as discerned through experimental testing and validation.
graphics processing units, mobile robots, processor scheduling
T. Amert, N. Otterness, M. Yang, J. H. Anderson and F. D. Smith, "GPU Scheduling on the NVIDIA TX2: Hidden Details Revealed," 2017 IEEE Real-Time Systems Symposium (RTSS), Paris, France, 2018, pp. 104-115.