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Latency Measurements for an Emulation Platform on Autonomous Driving Platform NVIDIA Drive PX2

机译:自主驾驶平台NVIDIA Drive PX2上的仿真平台的延迟测量

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The use of GPUs in the automotive sector is a possibility to provide a lot of computing power for complex algorithms required for autonomous driving. In order to be able to make statements about the real-time capability of algorithms, it is necessary to be able to make precise statements about the runtime behavior. This work deals with the execution time of instructions on the NVIDIA Drive PX2 evaluation platform designed for an automotive environment. It is to be shown what influence block and warp variables have on execution times and whether these values can be used to estimate the total runtime of algorithms. This provides a deeper insight into the functionality of the modern Pascal architecture.
机译:在汽车领域使用GPU可能为自动驾驶所需的复杂算法提供大量计算能力。为了能够发表关于算法实时能力的陈述,必须能够做出关于运行时行为的精确陈述。这项工作处理了针对汽车环境设计的NVIDIA Drive PX2评估平台上的指令执行时间。将显示对执行时间有什么影响的块和扭曲变量,以及这些值是否可用于估计算法的总运行时间。这提供了对现代Pascal架构功能的更深入的了解。

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