The development of mixed-criticality systems that integrate applications of different criticality levels (safety, security, real-time and non real-time) can provide multiple benefits such as product cost-size-weight reduction, reliability increase and scalability. However, the integration of applications with different criticality levels leads to several challenges with respect to safety certification standards. This paper defines a safety certification strategy for IEC-61508 compliant industrial mixedcriticality systems based on multicore partitioning. This approach is illustrated with a safety concept of a simplified IEC-61508 compliant wind-turbine mixed-criticality system, reviewed and approved by a certification authority.
Critical real-time systems require strict resource provisioning in terms of memory and timing. The constant need for higher performance in these systems has led industry to recently include GPUs. However, GPU software ecosystems are by their nature closed source, forcing system engineers to consider them as black boxes, complicating resource provisioning. In this work we reverse engineer the internal operations of the GPU system software to increase the understanding of their observed behaviour and how resources are internally managed. This way, we allow system engineers to accurately determine the exact amount of resources required by their critical systems, avoiding underprovisioning. We first apply our methodology on a wide range of GPU hardware showing its generality in obtaining the properties of the GPU memory allocators. Next, we demonstrate the benefits of such knowledge in resource provisioning of two case studies from the automotive domain, where the actual memory consumption is up to 5.6× more than the memory requested by the application.
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