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Exploring dataflow-based thread level parallelism in cyber-physical systems

Authors: Giorgi, Roberto;

Exploring dataflow-based thread level parallelism in cyber-physical systems

Abstract

Smart Cyber-Physical Systems (SCPS) aim not only at integrating computational platforms and physical processes, but also at creating larger "systems of systems" capable of satisfying multiple critical constraints such as energy efficiency, high-performance, safety, security, size and cost. The AXIOM project aims at designing such systems by focusing on low-cost Single Board Computers (SBC), based on current System-on-Chips (SoC) that include both programmable logic (FPGA), multi-core CPUs, accelerators and peripherals. A dataflow execution model, partially developed in the TERAFLUX project, brings a more predictable and reliable execution. The goals of AXIOM include: i) the possibility to easily program the system with a shared-memory model based on OmpSs; ii) the possibility of scaling up the system through a custom but inexpensive interconnect; iii) the possibility of accelerating a specific function on a single or multiple FPGAs of the system. The dataflow execution model operates at thread-level granularity. In this paper the AXIOM execution model and the related memory memory model is further detailed. The memory model is key for the execution of threads while reducing the need of data transfers. The preliminary results confirm the scalability of this model.

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Keywords

cyber-physical system, dataflow, distributed shared memory, programming model, scalability, thread-level parallelism

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
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