3.8 Proceedings Paper

GPU Scheduling on the NVIDIA TX2: Hidden Details Revealed

期刊

出版社

IEEE
DOI: 10.1109/RTSS.2017.00017

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资金

  1. NSF [CPS 1239135, CNS 1409175, CPS 1446631, CNS 1563845]
  2. AFOSR grant [FA9550-14-1-0161]
  3. ARO grant [W911NF-14-1-0499]
  4. General Motors
  5. Direct For Computer & Info Scie & Enginr
  6. Division Of Computer and Network Systems [1409175] Funding Source: National Science Foundation

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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.

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