Add to ORKGWe developed a theory in order to address crucial questions of program design methodology. We think that it could unify two concepts of data-parallel programming that we consider fundamental as they concern data locality expression: the notions of alignment in HPF and shape in C . Our wish is to provide a semantic domain where data-parallel statements can be systematically proved as well as efficiently implemented
The essence of data-parallelism is a O(1) map function. A data-parallel interpretation of map is the...
Data parallelislm is one of the more successful efforts to introduce explicit parallelism to high le...
The art of designing parallel programs is underdeveloped because we do not understand parallelism c...
International audienceWe developed a theory in order to address crucial questions of program design ...
Increased programmability for concurrent applications in distributed systems requires automatic supp...
Parallel programs mainly differ from sequential ones in that they include geometrical aspects involv...
Parallel programming is hard and programmers still struggle to write code for shared memory multicor...
The success of parallel architectures has been limited by the lack of high-level parallel programmin...
Data-parallel languages, such as H scIGH P scERFORMANCE F scORTRAN or F scORTRAN D, provide a machin...
Computing Model = Execution Model + Programming Model In the world of sequential computing, much wo...
AbstractWe propose a set-theoretic model for parallelism. The model is based on separate distributio...
. Data-parallel languages, in particular HPF, provide a highlevel view of operators overs parallel d...
. Most data-parallel languages use arrays to support parallelism. This regular data structure allows...
Research on programming distributed memory multiprocessors has resulted in a well-understood program...
Data locality is a well-recognized requirement for the development of any parallel application, but ...
The essence of data-parallelism is a O(1) map function. A data-parallel interpretation of map is the...
Data parallelislm is one of the more successful efforts to introduce explicit parallelism to high le...
The art of designing parallel programs is underdeveloped because we do not understand parallelism c...
International audienceWe developed a theory in order to address crucial questions of program design ...
Increased programmability for concurrent applications in distributed systems requires automatic supp...
Parallel programs mainly differ from sequential ones in that they include geometrical aspects involv...
Parallel programming is hard and programmers still struggle to write code for shared memory multicor...
The success of parallel architectures has been limited by the lack of high-level parallel programmin...
Data-parallel languages, such as H scIGH P scERFORMANCE F scORTRAN or F scORTRAN D, provide a machin...
Computing Model = Execution Model + Programming Model In the world of sequential computing, much wo...
AbstractWe propose a set-theoretic model for parallelism. The model is based on separate distributio...
. Data-parallel languages, in particular HPF, provide a highlevel view of operators overs parallel d...
. Most data-parallel languages use arrays to support parallelism. This regular data structure allows...
Research on programming distributed memory multiprocessors has resulted in a well-understood program...
Data locality is a well-recognized requirement for the development of any parallel application, but ...
The essence of data-parallelism is a O(1) map function. A data-parallel interpretation of map is the...
Data parallelislm is one of the more successful efforts to introduce explicit parallelism to high le...
The art of designing parallel programs is underdeveloped because we do not understand parallelism c...