Fundamentals of digital image processing
Fundamentals of digital image processing
Algorithmic skeletons: structured management of parallel computation
Algorithmic skeletons: structured management of parallel computation
Algebra of programming
Arrays, Functional Languages and Parallel Systems
Arrays, Functional Languages and Parallel Systems
Introduction to Functional Programming
Introduction to Functional Programming
Skeletons for Data Parallelism in p3l
Euro-Par '97 Proceedings of the Third International Euro-Par Conference on Parallel Processing
Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
Skeletons for parallel image processing: an overview of the SKIPPER project
Parallel Computing - Special issue: Advanced environments for parallel and distributed computing
Patterns and skeletons for parallel and distributed computing
Patterns and skeletons for parallel and distributed computing
QR factorization with Morton-ordered quadtree matrices for memory re-use and parallelism
Proceedings of the ninth ACM SIGPLAN symposium on Principles and practice of parallel programming
A library of constructive skeletons for sequential style of parallel programming
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
Flexible skeletal programming with eskel
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
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Computations on two-dimensional arrays such as matrices and images are one of the most fundamental and ubiquitous things in computational science and its vast application areas, but development of efficient parallel programs on two-dimensional arrays is known to be hard. To solve this problem, we have proposed a skeletal framework on two-dimensional arrays based on the theory of constructive algorithmics. It supports users, even with little knowledge about parallel machines, to develop systematically both correct and efficient parallel programs on two-dimensional arrays. In this paper, we apply our framework to the matrix-convolutions often used in image filters and difference methods. We show the efficacy of the framework by giving a general parallel program for the matrix-convolutions described with the skeletons, and a theorem that optimizes the general program into an application-specific one.