Several researchers have looked into various issues related to automatic parallelization of sequential programs for multicomputers. But there is a need for a coherent framework which encompasses all these issues. In this paper we present a such a framework which takes best advantage of the multicomputer architecture. We resort to tiling transformation for iteration space partitioning and propose a scheme of automatic data partitioning and dynamic data distribution. We have tried a simple implementation of our scheme on a transputer based multicomputer [1] and the results are encouraging
Abstract. In this paper we present a system that automatically partitions sequential divide{and{conq...
This paper describes ASPAR (Automatic and Symbolic PARallelization) which consists of a source-to-so...
Massively Parallel Processor systems provide the required computational power to solve most large sc...
Several researchers have looked into various issues related to automatic parallelization of sequenti...
Divide--and--conquer algorithms obtain the solution to a given problem by dividing it into subproble...
Parallel computing hardware is affordable and accessible, yet parallel programming is not as widespr...
Divide{and{conquer algorithms obtain the solution to a given problem by dividing it into subproblems...
On shared memory parallel computers (SMPCs) it is natural to focus on decomposing the computation (...
Parallel architectures with physically distributed memory providing computing cycles and large amoun...
In order to utilize parallel computers, four approaches, broadly speaking, to the provision of paral...
Parallelizing compilers have emerged to be a useful tool in the development of parallel programs. Mo...
Shared-memory multiprocessor systems can achieve high performance levels when appropriate work paral...
In this paper, we prove that the data-driven parallelization technique, which compiles sequential pr...
Optimal multiple sequence alignment by dynamic programming, like many highly dimensional scientific ...
Recent advances in polyhedral compilation technology have made it feasible to automatically transfor...
Abstract. In this paper we present a system that automatically partitions sequential divide{and{conq...
This paper describes ASPAR (Automatic and Symbolic PARallelization) which consists of a source-to-so...
Massively Parallel Processor systems provide the required computational power to solve most large sc...
Several researchers have looked into various issues related to automatic parallelization of sequenti...
Divide--and--conquer algorithms obtain the solution to a given problem by dividing it into subproble...
Parallel computing hardware is affordable and accessible, yet parallel programming is not as widespr...
Divide{and{conquer algorithms obtain the solution to a given problem by dividing it into subproblems...
On shared memory parallel computers (SMPCs) it is natural to focus on decomposing the computation (...
Parallel architectures with physically distributed memory providing computing cycles and large amoun...
In order to utilize parallel computers, four approaches, broadly speaking, to the provision of paral...
Parallelizing compilers have emerged to be a useful tool in the development of parallel programs. Mo...
Shared-memory multiprocessor systems can achieve high performance levels when appropriate work paral...
In this paper, we prove that the data-driven parallelization technique, which compiles sequential pr...
Optimal multiple sequence alignment by dynamic programming, like many highly dimensional scientific ...
Recent advances in polyhedral compilation technology have made it feasible to automatically transfor...
Abstract. In this paper we present a system that automatically partitions sequential divide{and{conq...
This paper describes ASPAR (Automatic and Symbolic PARallelization) which consists of a source-to-so...
Massively Parallel Processor systems provide the required computational power to solve most large sc...