GPUs have been shown to cover the computing performance needs of autonomous driving (AD) systems. However, since the GPUs used for AD build on designs for the mainstream market, they may lack fundamental properties for correct operation under automotive's safety regulations. In this paper, we analyze some of the main challenges in hardware and software design to embrace GPUs as the reference computing solution for AD, with emphasis in ISO 26262 functional safety requirements.
Autonomous Driving (AD) imposes the use of highperformance hardware, such as GPUs, to perform object recognition and tracking in real-time. However, differently to the consumer electronics market, critical real-time AD functionalities require a high degree of resilience against faults, in line with the automotive ISO26262 functional safety standard requirements. ISO26262 imposes the use of some source of independent redundancy for the most critical functionalities so that a single fault cannot lead to a failure, being dual core lockstep (DCLS) with diversity the preferred choice for computing devices. Unfortunately, GPUs do not support diverse DCLS by construction, thus failing to meet ISO26262 requirements efficiently. In this paper we propose lightweight modifications to GPUs to enable diverse DCLS for critical real-time applications without diminishing their performance for non-critical applications. In particular, we show how enabling specific mechanisms for software-controlled kernel scheduling in the GPU, allows guaranteeing that redundant kernels can be executed in different resources so that a single fault cannot lead to a failure, as imposed by ISO26262. Our results on a GPU simulator and an NVIDIA GPU prove the viability of the approach and its effectiveness on high-performance GPU designs needed for AD systems.
Safety-related systems, such as those in automotive, avionics and space, impose the existence of appropriate safety measures to meet the safety requirements of the system. In the case of the highest integrity level functionalities (e.g. ASIL-D in automotive), diverse redundancy must be deployed to avoid unreasonable risk of a single fault leading the system to a failure (e.g. using lockstepped cores). However, existing lockstep solutions are either (1) highly intrusive and inflexible coupling two cores with hardware means, or (2) costly in terms of execution time and monitoring if a software monitor thread checks that cores running redundantly preserve sufficient staggering.This paper presents SafeDE, a Diversity Enforcement hardware module providing light-lockstep support by means of a non-intrusive and flexible hardware module that preserves staggering across cores running redundant threads, thus bringing time diversity. SafeDE reconciles the lightness and flexibility of software-only solutions, even allowing using the cores without any lockstepping, as well as the tighter staggering of hardware-only solutions that allow using staggering values of few cycles, instead of hundreds of microseconds, as for software-only solutions. Our integration of SafeDE in a RISC-V FPGA-based space multicore from Cobham Gaisler shows that staggering is effectively preserved, and SafeDE overheads are negligible in terms of area and performance due to staggering. 1 Available as an open-source component in https://bsccaos.github.io [6].
Following the trend of other safety-critical industries like automotive and avionics, the space domain is witnessing an increase in the on-board computing performance demands. This raise in performance needs comes from both control and payload parts of the spacecraft and calls for advanced electronics systems able to provide high computational power under the constraints of the harsh space environment. On the non-technical side, for strategic reasons it is mandatory to get European independence on the used computing technology. In this project, we study the applicability of embedded GPUs in space, which have shown a dramatic improvement of their performance per-watt ratio coming from their proliferation in consumer markets based on competitive European technology. To that end, we perform an analysis of the existing space application domains to identify which software domains can benefit from their use. Moreover, we survey the embedded GPU domain in order to assess whether embedded GPUs can provide the required computational power and identify the challenges which need to be addressed for their adoption in space. In this paper, we describe the steps followed in the project, as well as a summary of results obtained from our analyses so far in the project.
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