A Unified Cloud Platform for Autonomous Driving

被引：33
|
作者：
Liu, Shaoshan [1 ]
Tang, Jie [2 ]
Wang, Chao
Wang, Quan [3 ]
Gaudiot, Jean-Luc [4 ]
机构：
[1] PerceptIn, Sunnyvale, CA 94085 USA
[2] South China Univ Technol, Sch Comp Sci & Engn, Guangzhou, Guangdong, Peoples R China
[3] Baidu, Autonomous Driving Unit, Beijing, Peoples R China
[4] Univ Calif Irvine, Dept Elect Engn & Comp Sci, Irvine, CA USA
来源：
COMPUTER | 2017年 / 50卷 / 12期
基金：
美国国家科学基金会;
关键词：
Alluxio; autonomous vehicles; Baidu; BinPipeRDD; CNN; convolution neural network; distributed computing; distributed storage; Hadoop; Hadoop Distributed File System; HDFS; heterogeneous computing; LiDAR; Linux Containers; LXC; map generation; MapReduce; model training; OpenCL; Paddle; Parallel Distributed Deep Learning; RDD; resilient distributed dataset; Robot Operating System; ROS; self-driving cars; simulation testing; Spark; YARN;
D O I：
10.1109/MC.2017.4451224
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Tailoring cloud support for each autonomous-driving application would require maintaining multiple infrastructures, potentially resulting in low resource utilization, low performance, and high management overhead. To address this problem, the authors present a unified cloud infrastructure with Spark for distributed computing, Alluxio for distributed storage, and OpenCL to exploit heterogeneous computing resources for enhanced performance and energy efficiency.
引用
收藏
页码：42 / 49
页数：8
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