Abstract
An increasing number of real-time embedded applications present high computation requirements which need to be realized within strict time constraints. Simultaneously, architectures are becoming more and more heterogeneous, programming models are having difficulty in scaling or stepping outside of a particular domain, and programming such solutions requires detailed knowledge of the system and the skills of an experienced programmer. In this context, this paper advocates the transparent integration of a parallel and distributed execution framework, capable of meeting real-time constraints, based on OpenMP programming model, and using MPI as the distribution mechanism. The paper also introduces our modified implementation of GCC compiler, enabled to support such parallel and distributed computations, which is evaluated through a real implementation. This evaluation gives important hints, towards the development of the parallel/distributed fork-join framework for supporting real-time embedded applications.

Abstract
The ENCOURAGE project tionalizing energy usage in building by implementing a smart energy grid based on intelligent scheduling of energy consuming appliances, renewable energy production, and inter-building energy trading. This paper presents the reference architecture proposed in the context of the ENCOURAGE project, and relates it with the goals of its research efforts.

Abstract
Experts provided information about parallel and multicore systems in papers submitted and discussed at a workshop. Discussion followed about the wisdom of giving any directive further than with parallel for the programmers to control the details of how parallelism was configured, executed, and potentially mapped in the runtime. The counter argument was raised that in real-time systems there was a need for the programmer to specify such control to directly specify the behavior, which was required for behavior analysis and timing behavior analysis. Questions were raised about the memory model of the proposal, and it was decided that the general model was that which supported a shared memory system, with cache coherency and uniform access to memory= within a single partition.

Abstract

Abstract

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%.