Abstract

Abstract
The second session on the topic of Multiprocessor Issues reviewed and evaluated the efficacy of the Ada 2012 support in the area of multiprocessor resource control. Andy Wellings, the Chair presented a proposal of an API that allowed controlling and extending the queue locks, and implementing the access control protocols. In the second part of the session, Miguel Pinho started by presenting an overview of Transactional Memory (TM), providing a quick overview of how in this approach atomic sections are executed concurrently and speculatively, in isolation. In the third topic of the session, the Chair started by providing an overview of the Reference Manual wordings concerning the access and control protocols for Protected Objects, noting that both the RM and the Annotated Reference Manual (ARM) do not fully define the access protocol for a protected object on a multiprocessor system. Finally, in the last topic (parallel barriers in Protected Objects), the workshop concluded that this would be a good mechanism to have, but that a suitable approach needs further investigation.

Abstract

Abstract
The ELASTIC European project addresses the emergence of extreme-scale analytics, providing a software architecture with a new elasticity concept, intended to support smart cyber-physical systems with performance requirements from extreme-scale analytics workloads. One of the main challenges being tackled by ELASTIC is the necessity to simultaneously fulfil the non-functional properties inherited from smart systems, such as real-time, energy efficiency, communication quality or security. This paper presents how the ELASTIC architecture monitors and manages such non-functional requirements, working in close collaboration with the component responsible for the orchestration of elasticity. © 2022, Ada-Europe. All rights reserved.

Abstract
The automotive software industry is gradually introducing new functionalities and technologies that increase the efficiency, safety, and comfort of vehicles. These functionalities are quickly accepted by consumers; however, the consequences of this evolution are twofold. First, developing correct systems that integrate more applications and hardware is becoming more complex. To cope with this, new standards (such as Adaptive AUTOSAR) and frameworks (such as AMALTHEA) are being proposed, to assist the development of flexible systems based on high-performance electronic control units (ECU). Second, the increase of functionality is supported by a dramatic increase of electronic parts on automotive systems. Consequently, the impact of software on the electrical power and energy non-functional requirements of automotive systems has come under focus. In this paper we propose an automatic and self-contained approach that supplements a model of an automotive system described on the AMALTHEA platform with energy-related annotations. From the analysis of simulation (or execution) traces of the modelled software, we estimate the power consumption for each software component, on a target hardware platform. This method enables energy analysis during the entire development life-cycle; furthermore, it contributes for the development of energy management strategies for dynamic and self-adaptive systems. © 2022 IEEE.

Abstract
Designing cost-efficient multi-core real-time systems requires efficient techniques to allocate applications to cores while satisfying their timing constraints. However, existing approaches typically allocate using a First-Fit algorithm, which does not consider the execution time and potential parallelism of paths in the applications, resulting in over-dimensioned systems. This work addresses this problem by proposing a new heuristic algorithm, Critical-Path-First, for the allocation of real-time streaming applications modeled as dataflow graphs on 2D mesh multi-core processors. The main criteria of the algorithm is to allocate paths that have the highest impact on the execution time of the application first. It is also able to exploit parallelism in the application by allocating parallel paths on different cores. Experimental evaluation shows that the proposed heuristic improves the resource utilization by allocating up to 7% more applications and it minimizes the average end-to-end worst-case response time of the allocated applications by up to 31%.