Algorithmic skeletons: structured management of parallel computation
Algorithmic skeletons: structured management of parallel computation
Parallel algorithms: for digital image processing, computer vision and neural networks
Parallel algorithms: for digital image processing, computer vision and neural networks
Fortran M: a language for modular parallel programming
Journal of Parallel and Distributed Computing
A Framework for Exploiting Task and Data Parallelism on Distributed Memory Multicomputers
IEEE Transactions on Parallel and Distributed Systems
A task- and data-parallel programming language based on shared objects
ACM Transactions on Programming Languages and Systems (TOPLAS)
Compiler support for task scheduling in hierarchical execution models
Journal of Systems Architecture: the EUROMICRO Journal - Special issue on tools and environments for parallel program development
MPI-The Complete Reference, Volume 1: The MPI Core
MPI-The Complete Reference, Volume 1: The MPI Core
IEEE Transactions on Pattern Analysis and Machine Intelligence
CPR: Mixed Task and Data Parallel Scheduling for Distributed Systems
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
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The paper presents a data and task parallel environment for parallelizing low-level image processing applications on distributed memory systems. Image processing operators are parallelized by data decomposition using algorithmic skeletons. At the application level we use task decomposition, based on the Image Application Task Graph. In this way, an image processing application can be parallelized both by data and task decomposition, and thus beter speed-ups can be obtained. The framework is implemented using C and MPI-Panda library and it can be easily ported to other distributed memory systems.