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Model-based dynamic scheduling for multicore implementation of image processing systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Original languageEnglish
Title of host publication2017 IEEE International Workshop on Signal Processing Systems, SiPS 2017
ISBN (Electronic)9781538604465
Publication statusPublished - 14 Nov 2017
Publication typeA4 Article in a conference publication
EventIEEE International Workshop on Signal Processing Systems - Lorient, France
Duration: 3 Oct 20175 Oct 2017


ConferenceIEEE International Workshop on Signal Processing Systems


In this paper, we present a new software tool, called HTGS Model-based Engine (HMBE), for the design and implementation of multicore signal processing applications. HMBE provides complementary capabilities to HTGS (Hybrid Task Graph Scheduler), which is a recently-introduced software tool for implementing scalable workflows for high performance computing applications. HMBE integrates advanced design optimization techniques provided in HTGS with model-based approaches that are founded on dataflow principles. Such integration contributes to (a) making the application of HTGS more systematic and less time consuming, (b) incorporating additional dataflow-based optimization capabilities with HTGS optimizations, and (c) automating significant parts of the HTGS-based design process. In this paper, we present HMBE with an emphasis on novel dynamic scheduling techniques that are developed as part of the tool. We demonstrate the utility of HMBE through a case study involving an image stitching application for large scale microscopy images.