Efficient ROS-Compliant CPU-iGPU Communication on Embedded Platforms

Author:

De Marchi MircoORCID,Lumpp FrancescoORCID,Martini EnricoORCID,Boldo MicheleORCID,Aldegheri StefanoORCID,Bombieri NicolaORCID

Abstract

Many modern programmable embedded devices contain CPUs and a GPU that share the same system memory on a single die. Such a unified memory architecture (UMA) allows programmers to implement different communication models between CPU and the integrated GPU (iGPU). Although the simpler model guarantees implicit synchronization at the cost of performance, the more advanced model allows, through the zero-copy paradigm, the explicit data copying between CPU and iGPU to be eliminated with the benefit of significantly improving performance and energy savings. On the other hand, the robot operating system (ROS) has become a de-facto reference standard for developing robotic applications. It allows for application re-use and the easy integration of software blocks in complex cyber-physical systems. Although ROS compliance is strongly required for SW portability and reuse, it can lead to performance loss and elude the benefits of the zero-copy communication. In this article we present efficient techniques to implement CPU–iGPU communication by guaranteeing compliance to the ROS standard. We show how key features of each communication model are maintained and the corresponding overhead involved by the ROS compliancy.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering

Reference21 articles.

1. A SURVEY OF TECHNIQUES FOR MANAGING AND LEVERAGING CACHES IN GPUs

2. Nvidia Tootlkit Documentation, Unified Memoryhttps://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#um-unified-memory-programming-hd

3. Performance Optimisation of Parallelized ADAS Applications in FPGA-GPU Heterogeneous Systems: A Case Study With Lane Detection

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