Algorithmic skeletons: structured management of parallel computation
Algorithmic skeletons: structured management of parallel computation
Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimized rapid prototyping for real-time embedded heterogeneous multiprocessors
CODES '99 Proceedings of the seventh international workshop on Hardware/software codesign
Fast prototyping of parallel-vision applications using functional skeletons
Machine Vision and Applications
Embodying Parallel Functional Skeletons: An Experimental Implementation on Top of MPI
Euro-Par '97 Proceedings of the Third International Euro-Par Conference on Parallel Processing
CAMLFLOW: a CAML to data-flow graph translator
Selected papers from the 2nd Scottish Functional Programming Workshop (SFP00)
Hi-index | 0.00 |
SKiPPER is a Skeleton-based Parallel Programming EnviRonment being developed since 1996 and running at LASMEA Laboratory, the Blaise-Pascal University, France. The main goal of the project was to demonstrate the applicability of skeleton-based parallel programming techniques to the fast prototyping of reactive vision applications. This paper deals with the special features embedded in the latest version of the project: algorithmic skeleton nesting capabilities and a fully dynamic operating model. Throughout the case study of a complete and realistic image processing application, in which we have pointed out the requirement for skeleton nesting, we are presenting the operating model of this feature. The work described here is one of the few reported experiments showing the application of skeleton nesting facilities for the parallelisation of a realistic application, especially in the area of image processing. The image processing application we have chosen is a 3D face-tracking algorithm from appearance.