Add to ORKGA large class of scientific and engineering applications may be classified as irregular and loosely synchronous from the perspective of parallel processing. We present a partial classification of such problems. This classification has motivated us to enhance Fortran D to provide language support for irregular, loosely synchronous problems. We present techniques for parallelization of such problems in the context of Fortran D
Irregular computation problems underlie many important scientific applications. Although these probl...
Optimistic parallelization is a promising approach for the parallelization of irregular algorithms: ...
In adaptive irregular problems the data arrays are accessed via indirection arrays, and data access ...
A large class of scientific and engineering applications may be classified as irregular and loosely ...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/16...
Data-parallel languages, such as H scIGH P scERFORMANCE F scORTRAN or F scORTRAN D, provide a machin...
This paper presents methods that make it possible to efficiently support irregular problems using da...
Languages such as Fortran D provide irregular distribution schemes that can efficiently support irre...
Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para ob...
Abstract. A problem is irregular if its solution requires the computa-tion of some properties for ea...
Irregularity arises in different contexts and causes different problems in parallel computing. We di...
In many scientific applications, arrays containing data are indirectly indexed through indirection a...
Automatic parallelization is usually believed to be less effective at exploiting implicit parallelis...
We present a general data parallel formulation for highly irregular problems in High Performance For...
Data parallel languages like High Performance Fortran (HPF) are emerging as the architecture indepen...
Irregular computation problems underlie many important scientific applications. Although these probl...
Optimistic parallelization is a promising approach for the parallelization of irregular algorithms: ...
In adaptive irregular problems the data arrays are accessed via indirection arrays, and data access ...
A large class of scientific and engineering applications may be classified as irregular and loosely ...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/16...
Data-parallel languages, such as H scIGH P scERFORMANCE F scORTRAN or F scORTRAN D, provide a machin...
This paper presents methods that make it possible to efficiently support irregular problems using da...
Languages such as Fortran D provide irregular distribution schemes that can efficiently support irre...
Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para ob...
Abstract. A problem is irregular if its solution requires the computa-tion of some properties for ea...
Irregularity arises in different contexts and causes different problems in parallel computing. We di...
In many scientific applications, arrays containing data are indirectly indexed through indirection a...
Automatic parallelization is usually believed to be less effective at exploiting implicit parallelis...
We present a general data parallel formulation for highly irregular problems in High Performance For...
Data parallel languages like High Performance Fortran (HPF) are emerging as the architecture indepen...
Irregular computation problems underlie many important scientific applications. Although these probl...
Optimistic parallelization is a promising approach for the parallelization of irregular algorithms: ...
In adaptive irregular problems the data arrays are accessed via indirection arrays, and data access ...