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A Processor Workload Distribution Algorithm for Massively Parallel Applications

Abstract : Directed Acyclic Graph (DAG) is a standard model used to describe tasks that execute according to precedence constraints and that allows intra-task parallelism. This model is well suited to camera-based applications where multiple treatments must be executed in parallel according to the camera input, such applications found for example in self-driving cars or image recognition via convolutional neural network (CNN). Such applications are used on embedded systems and therefore require low energy cost and a limited hardware space. The main contribution of this paper is to present a new partitioning algorithm based on a DAG stretching technique. This stretching algorithm frees processor cores and thus implies energy savings and leads to new hardware design using a reduced number of processors. We present an experimental evaluation of this algorithm to show its efficiency.
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Contributor : Serge Midonnet <>
Submitted on : Tuesday, May 29, 2018 - 6:58:31 AM
Last modification on : Wednesday, February 26, 2020 - 7:06:07 PM



Serge Midonnet, Achille Wattelar. A Processor Workload Distribution Algorithm for Massively Parallel Applications. 2016 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW), Oct 2016, Los Angeles, France. ⟨10.1109/SBAC-PADW.2016.13⟩. ⟨hal-01802109⟩



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