Homomorphisms are functions which can be parallelized by the divide-and-conquer paradigm. A class of distributable homomorphisms (DH) is introduced and an efficient parallel implementation schema for all functions of the class is derived by transformations in the Bird-Meertens formalism. The schema can be directly mapped on the hypercube with an unlimited or an arbitrary fixed number of processors, providing provable correctness and predictable performance. The popular scan-function (parallel prefix) illustrates the presentation: the systematically derived implementation for scan coincides with the practically used "folklore" algorithm for distributed-memory machines
Homology computations form an important step in topological data analysis that helps to identify con...
Polymorphism in programming languages enables code reuse. Here, we show that polymorphism has broad ...
. Algorithmic skeletons are polymorphic higher-order functions representing common parallelization p...
AbstractHomomorphisms are functions that match the divide-and-conquer pattern and are widely used in...
Abstract. MapReduce is a useful and popular programming model for data-intensive distributed paralle...
This paper describes several parallel algorithms that solve geometric problems. The algorithms are b...
Abstract. Algorithmic skeletons in conjunction with list homomorph-isms play an important role in fo...
International audienceSyDPaCC is a set of libraries for the Coq proof assistant. It allows to write ...
It is widely recognized that a key problem of parallel computation is in the development of both eff...
We present a family of parallel algorithms for simple language recognition problems involving bracke...
Mapping of parallel programs onto parallel computers for efficient execution is a fundamental proble...
Mapping of parallel programs onto parallel computers for efficient execution is a fundamental proble...
Function h on lists is a list homomorphism, if h [a] = f a h (x ++ y) = h x h y for some . Proper...
Persistent homology is a popular and powerful tool for capturing topological features of data. Advan...
Research Report RR-2010-01With the current generalization of parallel architectures arises the conce...
Homology computations form an important step in topological data analysis that helps to identify con...
Polymorphism in programming languages enables code reuse. Here, we show that polymorphism has broad ...
. Algorithmic skeletons are polymorphic higher-order functions representing common parallelization p...
AbstractHomomorphisms are functions that match the divide-and-conquer pattern and are widely used in...
Abstract. MapReduce is a useful and popular programming model for data-intensive distributed paralle...
This paper describes several parallel algorithms that solve geometric problems. The algorithms are b...
Abstract. Algorithmic skeletons in conjunction with list homomorph-isms play an important role in fo...
International audienceSyDPaCC is a set of libraries for the Coq proof assistant. It allows to write ...
It is widely recognized that a key problem of parallel computation is in the development of both eff...
We present a family of parallel algorithms for simple language recognition problems involving bracke...
Mapping of parallel programs onto parallel computers for efficient execution is a fundamental proble...
Mapping of parallel programs onto parallel computers for efficient execution is a fundamental proble...
Function h on lists is a list homomorphism, if h [a] = f a h (x ++ y) = h x h y for some . Proper...
Persistent homology is a popular and powerful tool for capturing topological features of data. Advan...
Research Report RR-2010-01With the current generalization of parallel architectures arises the conce...
Homology computations form an important step in topological data analysis that helps to identify con...
Polymorphism in programming languages enables code reuse. Here, we show that polymorphism has broad ...
. Algorithmic skeletons are polymorphic higher-order functions representing common parallelization p...