International audienceIn this paper, we show that various concepts and tools developed in the 90's in the field of data-parallelism provide a relevant spatial programming framework. It allows high level spatial computation specifications to be translated into efficient low-level operations on processing units. We provide some short examples to illustrate this statement
Computing increasingly happens somewhere, with that geographic location important to the computation...
Data-parallel primitives for performing operations on the PM1 quadtree, bucket PMR quadtree, and R-t...
Spatial association measures, when computed for large data sets, have significant computational requ...
International audienceIn this paper, we show that various concepts and tools developed in the 90's i...
Abstract—In this paper, we show that various concepts and tools developed in the 90’s in the field o...
Most parallel processing methods developed for geographic analyses bind the design of domain decompo...
We present the design rationale underlying a language for spatial computing and sketch a prototypica...
We present the design rationale underlying a language for spatial computing and sketch a prototypica...
ii Vector Spatial data types such as lines, polygons or regions etc usually comprises of hundreds of...
abstract: Nearly 25 years ago, parallel computing techniques were first applied to vector spatial an...
Emerging distributed computing scenarios call for novel autonomic approaches to distributed systems ...
Future ubiquitous computing environments will consist of massive, ad hoc networks of embedded system...
In computer science, dependence analysis determines whether or not it is safe to parallelize stateme...
International audienceThe current trend in electronics is to integrate more and more transistors on ...
Computing tasks may be parallelized top-down by splitting into per-node chunks when the tasks permit...
Computing increasingly happens somewhere, with that geographic location important to the computation...
Data-parallel primitives for performing operations on the PM1 quadtree, bucket PMR quadtree, and R-t...
Spatial association measures, when computed for large data sets, have significant computational requ...
International audienceIn this paper, we show that various concepts and tools developed in the 90's i...
Abstract—In this paper, we show that various concepts and tools developed in the 90’s in the field o...
Most parallel processing methods developed for geographic analyses bind the design of domain decompo...
We present the design rationale underlying a language for spatial computing and sketch a prototypica...
We present the design rationale underlying a language for spatial computing and sketch a prototypica...
ii Vector Spatial data types such as lines, polygons or regions etc usually comprises of hundreds of...
abstract: Nearly 25 years ago, parallel computing techniques were first applied to vector spatial an...
Emerging distributed computing scenarios call for novel autonomic approaches to distributed systems ...
Future ubiquitous computing environments will consist of massive, ad hoc networks of embedded system...
In computer science, dependence analysis determines whether or not it is safe to parallelize stateme...
International audienceThe current trend in electronics is to integrate more and more transistors on ...
Computing tasks may be parallelized top-down by splitting into per-node chunks when the tasks permit...
Computing increasingly happens somewhere, with that geographic location important to the computation...
Data-parallel primitives for performing operations on the PM1 quadtree, bucket PMR quadtree, and R-t...
Spatial association measures, when computed for large data sets, have significant computational requ...