Model-based dynamic scheduling for multicore implementation of image processing systems
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Title of host publication | 2017 IEEE International Workshop on Signal Processing Systems, SiPS 2017 |
| Publisher | IEEE |
| ISBN (Electronic) | 9781538604465 |
| DOIs | |
| Publication status | Published - 14 Nov 2017 |
| Publication type | A4 Article in a conference publication |
| Event | IEEE International Workshop on Signal Processing Systems - Lorient, France Duration: 3 Oct 2017 → 5 Oct 2017 |
Conference
| Conference | IEEE International Workshop on Signal Processing Systems |
|---|---|
| Country | France |
| City | Lorient |
| Period | 3/10/17 → 5/10/17 |
Abstract
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.