Towards transparent parallel/distributed support for real-time embedded applications

Garibay-Martínez, Ricardo; Ferreira, Luís Lino; Maia, Cláudio; Pinho, Luís Miguel

doi:10.1109/sies.2013.6601483

Cited by 3 publications

(4 citation statements)

References 5 publications

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“…The PDRT library makes the workload distribution between a set of distributed nodes. The PDRT library implements a for loop with parallel distributed real-time behaviour as the one described in (Garibay-Martínez et al, 2013a). The PDRT distributes the load in a for loop by following a similar behaviour as the example in Figure 6.6, that is, it evenly distributes the iterations in the for loop between the nodes in the system (the DST algorithm is not used.).…”

Section: Comparing Experimental Results and Simulation Resultsmentioning

confidence: 99%

“…Therefore, the MPI code is not seen by the programmer (the MPI code is implicitly called by the OpenMP library). The programmer only needs to specify which OpenMP code blocks to distribute by using the #pragma omp distributedParallel pragma, and specifying their deadlines , 2013a. This is illustrated in Algorithm 3.4, the for loop can be distributed among 3 threads and the computation must be completed before a deadline of 200 milliseconds.…”

Section: Supporting Parallel and Distributed Real-time Execution Withmentioning

confidence: 99%

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A Framework for the Development of Parallel and Distributed Real-Time Embedded Systems

Garibay-Martínez

Ferreira

Pinho

2012

2012 38th Euromicro Conference on Software Engineering and Advanced Applications

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Real-time embedded systems are part of our everyday life. These systems range from the traditional areas of military and mission critical to domestic and entertainment applications. The aim of real-time systems is to execute applications in a way that those applications met their temporal constraints. Most of the results for real-time systems are based on the sequential real-time execution model, where intra-task parallelism is forbidden. In the last decade real-time researchers have started to focus their attention on the case of multi-threaded parallel real-time task models. In these models, concurrent real-time activities are allowed to become parallel and to be processed in more than one processor at the same time. Despite the fact that parallel computations in multi-processors can offer an increased processing capacity, the multi-threaded parallel real-time task models have not considered the cases in which a distributed execution also exists. Such execution pattern can be used to provide even more capabilities and processing power. Furthermore, in some applications the use of parallel distributed computations is the only possibility in which the applications can comply with their time constraints. An example of such type of applications is modern automotive applications, which need to execute computational intensive applications (e.g., infotainment or driver assistance applications). Consequently, design frameworks that allow the workload to be distributed in peak situations by both parallel and distributed processors are required. Such scenarios require the integration of distributed computations with parallel real-time models. In a distributed system, the transmission delay of messages cannot be considered negligible as in the case of multi-processors systems, therefore, their impact on the schedulability of the system has to be considered. The fork-join Parallel/Distributed real-time (P/D task) model proposed in this thesis is designed to consider such execution pattern. P/D task model is derived from observing the execution of parallel and distributed programs (e.g. OpenMP, MPI). The thesis proposes a scheduling algorithm for P/D tasks, the Parallel/Distributed Deadline Monotonic Scheduling (P/D-DMS). The thesis also proposes two heuristics for task partitioning and priority assignment for the linear transactional model and the P/D tasks model, the Distributed using Optimal Priority Assignment (DOPA) heuristic and the Parallel-DOPA (P-DOPA) heuristic, respectively. A holistic analysis technique for P/D tasks is also proposed. The holistic approach allows to consider the systems as a whole, and an improved analysis is proposed based on that holistic view of the system. The allocation of P/D tasks is later extended by considering distributed multi-core nodes. The extension is based on the constraint programming approach. The analysis and iii iv proposals presented in this thesis are validated through simulations and an experimental evaluation.

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Section: Comparing Experimental Results and Simulation Resultsmentioning

confidence: 99%

Section: Supporting Parallel and Distributed Real-time Execution Withmentioning

confidence: 99%

A Framework for the Development of Parallel and Distributed Real-Time Embedded Systems

Garibay-Martínez

Ferreira

Pinho

2012

2012 38th Euromicro Conference on Software Engineering and Advanced Applications

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“…To this end, we are investigating more refined models such as ''limited-preemptive'' scheduling solutions which reduce the cache-related overhead without affecting the overall schedulability [37,36] as well as more dynamic techniques which try to balance those same effects against the load (e.g. work-stealing approaches [35,23,43]). …”

Section: T the Task Dependency Graphmentioning

confidence: 99%

P-SOCRATES: A parallel software framework for time-critical many-core systems

Pinho¹,

Quiñones

Bertogna

et al. 2015

Microprocessors and Microsystems

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Current generation of computing platforms is embracing multi-core and many-core processors to improve the overall performance of the system, meeting at the same time the stringent energy budgets requested by the market. Parallel programming languages are nowadays paramount to extracting the tremendous potential offered by these platforms: parallel computing is no longer a niche in the high performance computing (HPC) field, but an essential ingredient in all domains of computer science. The advent of next-generation many-core embedded platforms has the chance of intercepting a converging need for predictable high-performance coming from both the High-Performance Computing (HPC) and Embedded Computing (EC) domains. On one side, new kinds of HPC applications are being required by markets needing huge amounts of information to be processed within a bounded amount of time. On the other side, EC systems are increasingly concerned with providing higher performance in real-time, challenging the performance capabilities of current architectures. This converging demand raises the problem about how to guarantee timing requirements in presence of parallel execution.The paper presents how the time-criticality and parallelisation challenges are addressed by merging techniques coming from both HPC and EC domains, and provides an overview of the proposed framework to achieve these objectives. Current generation of computing platforms is embracing multi-core and many-core processors to improve the overall performance of the system, meeting at the same time the stringent energy budgets requested by the market. Parallel programming languages are nowadays paramount to extracting the tremendous potential offered by these platforms: parallel computing is no longer a niche in the high performance computing (HPC) field, but an essential ingredient in all domains of computer science. The advent of next-generation many-core embedded platforms has the chance of intercepting a converging need for predictable high-performance coming from both the High-Performance Computing (HPC) and Embedded Computing (EC) domains. On one side, new kinds of HPC applications are being required by markets needing huge amounts of information to be processed within a bounded amount of time. On the other side, EC systems are increasingly concerned with providing higher performance in real-time, challenging the performance capabilities of current architectures. This converging demand raises the problem about how to guarantee timing requirements in presence of parallel execution. The paper presents how the time-criticality and parallelisation challenges are addressed by merging techniques coming from both HPC and EC domains, and provides an overview of the proposed framework to achieve these objectives. P-SOCRATES

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“…Some of the most popular programming models implementing the fork-join structure are the OpenMP programming model [7], and the Message Passing Interface (MPI) model [8]. However, none of these programming models is able to provide any time guarantees, although some efforts on bridging that gap have been presented in [9,10].…”

Section: Introductionmentioning

confidence: 99%

On the scheduling of fork-join parallel/distributed real-time tasks

Garibay-Martínez

Nelissen

Ferreira

et al. 2014

Proceedings of the 9th IEEE International Symposium on Industrial Embedded Systems (SIES 2014)

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Modern real-time embedded applications present high computation requirements which need to be realized within strict time constraints. The current trend towards parallel processing in the embedded domain allows providing higher processing power. However, in some embedded applications, the use of powerful enough multi-core processors, may not be possible due to energy, space or cost constraints. A solution for this problem is to extend the parallel execution of the applications, allowing them to distribute their workload among networked nodes, on peak situations, to remote neighbour nodes in the system. In this context, we present the Partitioned-Distributed-Deadline Monotonic Scheduling algorithm for fork-join parallel/distributed fixed-priority tasks. We study the problem of scheduling fork-join tasks that execute in a distributed system, where the inherent transmission delay of tasks must be considered and cannot be deemed negligible, as in the case of multicore systems. Our scheduling algorithm is shown to have a resource augmentation bound of 4, which implies that any task set that is feasible on m unit-speed processors and a single shared real-time network, can be scheduled by our algorithm on m processors and a single real-time network that are 4 times faster. We confirm through simulations our analytical results.

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Towards transparent parallel/distributed support for real-time embedded applications

Cited by 3 publications

References 5 publications

A Framework for the Development of Parallel and Distributed Real-Time Embedded Systems

A Framework for the Development of Parallel and Distributed Real-Time Embedded Systems

P-SOCRATES: A parallel software framework for time-critical many-core systems

On the scheduling of fork-join parallel/distributed real-time tasks

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