Parallel SOftware framework for time-CRitical mAny-core sysTEmS

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High-performance parallelisation of real-time applications

Publication . Pinho, Luís Miguel; Nelis, Vincent; Quinoñes, Eduardo; Burgio, Paolo; Marongiu, Andrea; Gai, Paolo; Sancho, Juan

This paper presents an overview of the P-SOCRATES methodology and tools, instantiated in the UpScale SDK (Software Development Kit) for the development of time-predictable high-performance applications. The proposed methodology was designed to provide an integrated SDK to fully exploit the huge performance opportunities brought by the most advanced many-core processors, whilst ensuring a predictable performance and maintaining (or even reducing) development costs of applications. The paper also provides the performance results of the application of the SDK in relevant embedded usecases.

2017Conference object

Open access

Reduction of Parallel Computation in the Parallel Model for Ada

Publication . Taft, S. Tucker; Moore, Brad; Pinho, Luís Miguel; Michell, Stephen

One of the most common program constructs to be parallelized (and where most of the times gains are obtained) is parallel loops. This paper discusses different approaches to support loop parallelization in the fine-grained parallelism model for Ada currently being proposed, focusing in particular in the issues related to reducing operations.

2016Conference object

Restricted access

Response Time Analysis of Sporadic DAG Tasks under Partitioned Scheduling

Publication . Fonseca, José; Nelissen, Geoffrey; Nelis, Vincent; Pinho, Luís Miguel

Several schedulability analyses have been proposed for a variety of parallel task systems with real-time constraints. However, these analyses are mostly restricted to global scheduling policies. The problem with global scheduling is that it adds uncertainty to the lower-level timing analysis which on multicore systems are heavily context-dependent. As parallel tasks typically exhibit intense communication and concurrency among their sequential computational units, this problem is further exacerbated. This paper considers instead the schedulability of partitioned parallel tasks. More precisely, we present a response time analysis for sporadic DAG tasks atop multiprocessors under partitioned fixed-priority scheduling. We assume the partitioning to be given. We show that a partitioned DAG task can be modeled as a set of self-suspending tasks. We then propose an algorithm to traverse a DAG and characterize such worst-case scheduling scenario. With minor modifications, any state-of-the-art technique for sporadic self-suspending tasks can thus be used to derived the worstcase response time of a partitioned DAG task. Experiments show that the proposed approach significantly tightens the worst-case response time of partitioned parallel tasks comparatively to the state-of-the-art when the most accurate technique is chosen.

2016Conference object

Restricted access

Parallel Software Framework for Time-Critical many-core Systems

Publication . Pinho, Luís Miguel

Critical real-time embedded systems demand for more and more computational performance to process big amounts of data from multiple data sources with guaranteed processing response times.

2016Other

Open access

The variability of application execution times on a multi-core platform

Publication . Nelis, Vincent; Yomsi, Patrick; Pinho, Luís Miguel

It is a known fact that processes running concurrently on different cores in a multicore environment interfere with each other on the processor shared resources. The contention on these shared resources considerably slows down the execution on every core since sometimes the cores must stall while their requests to access the resources are being served. But by how much the execution may b e s lowed down due to this interference? In this pap er we answer this question with numbers coming from experimentation. That is, we quantify the magnitude of the impact of the interference on the execution time by running programs taken from the TACLeBench benchmark suite, a popular benchmark suite in the real-time research community, on the first generation of Kalray manycore processor family, the MPPA-256 (the development board) that goes by the code name “Andey”.

2016Conference object

Open access