In this paper, we investigate the single event effects under proton irradiation for the state-of-the-art embedded GPU NVIDIA Jetson Orin NX System-on-Module (SoM). Designed for deployment across safety critical domains and in particularly automotive, this system represents a cutting-edge advancement in high performance embedded computing with functional safety features, which makes it an ideal candidate for use in space systems. Our study evaluates the Single-Event Effects (SEE) manifested within the SoM’s central processing unit (CPU), graphics processing unit (GPU), and associated peripherals. Through our analysis, we aim to delineate the origins of Single Event Functional Interrupts (SEFI) occurring at the SoM level. Furthermore, we provide a detailed exposition on the errors observed within the GPU complex, elucidating the requisite conditions for their manifestation. Unlike previous works which treat embedded GPUs under irradiation as black box, we are able to identify the source of SEEs through ARM’s RAS subsystem, and observe for the first time in literature GPU SEEs. Our investigation culminates in a comprehensive assessment of the SoM’s susceptibility, identifying particularly sensitive components.

Recently the ASIC industry experiences a massive change with more and more small and medium businesses entering the custom ASIC development. This trend is fueled by the recent open hardware movement and relevant government and privately funded initiatives. These new developments can open new opportunities in the space sector – which is traditionally characterised by very low volumes and very high non-recurrent (NRE) costs – if we can show that the produced chips have favourable radiation properties. In this paper, we describe the design and tape-out of Space Shuttle, the first test chip for the evaluation of the suitability of the SkyWater 130nm PDK and the OpenLane EDA toolchain using the Google/E-fabless shuttle run for future space processors.

Embedded systems in critical domains, such as auto-motive, aviation, space domains, are often required to guarantee both functional and temporal correctness. Considering transient faults, fault analysis and mitigation approaches are implemented at various levels of the system design, in order to maintain the functional correctness. However, transient faults and their mitigation methods have a timing impact, which can affect the temporal correctness of the system. In this work, we expose the functional and the timing implications of transient faults for critical systems. More precisely, we initially highlight the timing effect of transient faults occurring in the combinational and sequential logic of a processor. Furthermore, we propose a full stack vulnerability analysis that drives the design of selective hardware-based mitigation for real-time applications. Last, we study the timing impact of software-based reliability mitigation methods applied in a COTS GPU, using a fault tolerant middleware.

In this paper we characterise two embedded GPU devices from the NVIDIA Xavier family System-on-Chip (SoC) using a proton beam. We compare the NVIDIA Xavier NX and Industrial devices, that respectively target commercial and automotive applications. We evaluate the Single-Event Effect (SEE) rate of both modules and their sub-components, both the CPU and GPU, using different power modes, and we try for the first time to identify their exact sources using the on-line testing facilities included in their ARM based system. Our conclusion is that the most sensitive part of the CPU complex of the SoC is the tag array of the various cache structures, while no errors were observed in the GPU, probably because of its fast execution compared to the CPU part of the application during the radiation campaign.

Embedded GPUs have been identified from both private and government space agencies as promising hardware technologies to satisfy the increased needs of payload processing. The GPU4S (GPU for Space) project funded from the European Space Agency (ESA) has explored in detail the feasibility and the benefit of using them for space workloads. Currently at the closing phases of the project, in this paper we describe the main project outcomes and explain the lessons we learnt. In addition, we provide some guidelines for the next steps towards their adoption in space.

On-board processing requirements of future space missions are constantly increasing, calling for new hardware than the traditional ones used in space. Embedded GPUs are an attractive candidate offering both high performance capabilities and low power consumption, but there are no complex industrial case studies from the space domain demonstrating these advantages. In this paper we present the GPU parallelisation of an on-board algorithm, as well as its performance on a promising embedded GPU COTS platform targeting critical systems.

Following the same trend of 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 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, which is still in its early phases, 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 to be followed in the project, as well as the results of our preliminary analyses in the first months of the project.