. Most data-parallel languages use arrays to support parallelism. This regular data structure allows a natural development of regular parallel algorithms. The implementation of irregular algorithms requires a programming effort to project the irregular data structures onto regular structures. We first propose in this paper a classification of existing data-parallel languages. We briefly describe their irregular and dynamic aspects, and derive different levels where irregularity and dynamicity may be introduced. We propose then a new irregular and dynamic data-parallel programming model, called Idole. Finally we discuss its integration in the C++ language, and present an overview of the Idole extension of C++. 1 Irregularity and Data-Paralle...
In this paper, we present a novel method for parallelizing imperative programs in the presence of dy...
Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel c...
The last several years have seen multicore architectures become ascendant in the computing world. As...
Data-parallelism is considered as a paradigm that can solve many difficulties of parallel programmin...
The success of parallel architectures has been limited by the lack of high-level parallel programmin...
This paper describes the integration of nested data parallelism into imperative languages using the ...
. Data-parallel languages, in particular HPF, provide a highlevel view of operators overs parallel d...
. The main motivation of 81/2 is to develop a high-level language that supports the parallel simulat...
Parallel computing hardware is ubiquitous, ranging from cell-phones with multiple cores to super-com...
Data-parallel languages, such as H scIGH P scERFORMANCE F scORTRAN or F scORTRAN D, provide a machin...
Irregularity arises in different contexts and causes different problems in parallel computing. We di...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/16...
We developed a theory in order to address crucial questions of program design methodology. We think ...
Abstract. Much work has been done in the areas of and-parallelism and data-parallelism in Logic Prog...
Data-parallel programming is more important than ever since serial performance is stagnating. All ma...
In this paper, we present a novel method for parallelizing imperative programs in the presence of dy...
Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel c...
The last several years have seen multicore architectures become ascendant in the computing world. As...
Data-parallelism is considered as a paradigm that can solve many difficulties of parallel programmin...
The success of parallel architectures has been limited by the lack of high-level parallel programmin...
This paper describes the integration of nested data parallelism into imperative languages using the ...
. Data-parallel languages, in particular HPF, provide a highlevel view of operators overs parallel d...
. The main motivation of 81/2 is to develop a high-level language that supports the parallel simulat...
Parallel computing hardware is ubiquitous, ranging from cell-phones with multiple cores to super-com...
Data-parallel languages, such as H scIGH P scERFORMANCE F scORTRAN or F scORTRAN D, provide a machin...
Irregularity arises in different contexts and causes different problems in parallel computing. We di...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/16...
We developed a theory in order to address crucial questions of program design methodology. We think ...
Abstract. Much work has been done in the areas of and-parallelism and data-parallelism in Logic Prog...
Data-parallel programming is more important than ever since serial performance is stagnating. All ma...
In this paper, we present a novel method for parallelizing imperative programs in the presence of dy...
Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel c...
The last several years have seen multicore architectures become ascendant in the computing world. As...