GPU Scheduling on the NVIDIA TX2: Hidden Details Revealed

被引：121

作者：

Amert, Tanya ^{[1
]}

Otterness, Nathan ^{[1
]}

Yang, Ming ^{[1
]}

Anderson, James H. ^{[1
]}

Smith, F. Donelson ^{[1
]}

机构：

[1] Univ N Carolina, Dept Comp Sci, Chapel Hill, NC 27599 USA

来源：

2017 IEEE REAL-TIME SYSTEMS SYMPOSIUM (RTSS) | 2017年

基金：

美国国家科学基金会;

关键词：

D O I：

10.1109/RTSS.2017.00017

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：104 / 115

页数：12