Add to ORKGEnhancing high performance computing on distributed computers asks for a programming environment to help users write their parallel applications correctly, efficiently and easily. One of the open challenges for PVM is to generate parallel code from a serial program. In this contribution, a tool is presented to extract parallelism in loops with no loop-carried dependencies. Then code is generated to distribute computations and the data of the parallel loops over cooperating PVM computers
Shared-memory multiprocessor systems can achieve high performance levels when appropriate work paral...
The shared-memory programming model can be an effective way to achieve parallelism on shared memory ...
This work leverages an original dependency analysis to parallelize loops regardless of their form i...
Modern computers will increasingly rely on parallelism to achieve high computation rates. Techniques...
Loops are the main source of parallelism in scientific programs. Hence, several techniques were dev...
PVM is a succesfull programming environment for distributed computing in the languages C and Fortran...
Abstract—Parallelization and locality optimization of affine loop nests has been successfully addres...
In this paper, we survey loop parallelization algorithms, analyzing the dependence representations t...
The Shared Virtual Memory (SVM) is an interesting layout that handles data storage, retrieval and co...
In this paper we present a unified approach for compiling programs for Distributed-Memory Multiproce...
AbstractSpeculative parallelization is a classic strategy for automatically parallelizing codes that...
Current parallelizing compilers cannot identify a significant fraction of parallelizable loops becau...
Current parallelizing compilers cannot identify a significant fraction of parallelizable loops becau...
A new technique to parallelize loops with variable distance vectors is presented. The method extends...
Abstract. This paper presents a compilation technique that performs automatic parallelization of can...
Shared-memory multiprocessor systems can achieve high performance levels when appropriate work paral...
The shared-memory programming model can be an effective way to achieve parallelism on shared memory ...
This work leverages an original dependency analysis to parallelize loops regardless of their form i...
Modern computers will increasingly rely on parallelism to achieve high computation rates. Techniques...
Loops are the main source of parallelism in scientific programs. Hence, several techniques were dev...
PVM is a succesfull programming environment for distributed computing in the languages C and Fortran...
Abstract—Parallelization and locality optimization of affine loop nests has been successfully addres...
In this paper, we survey loop parallelization algorithms, analyzing the dependence representations t...
The Shared Virtual Memory (SVM) is an interesting layout that handles data storage, retrieval and co...
In this paper we present a unified approach for compiling programs for Distributed-Memory Multiproce...
AbstractSpeculative parallelization is a classic strategy for automatically parallelizing codes that...
Current parallelizing compilers cannot identify a significant fraction of parallelizable loops becau...
Current parallelizing compilers cannot identify a significant fraction of parallelizable loops becau...
A new technique to parallelize loops with variable distance vectors is presented. The method extends...
Abstract. This paper presents a compilation technique that performs automatic parallelization of can...
Shared-memory multiprocessor systems can achieve high performance levels when appropriate work paral...
The shared-memory programming model can be an effective way to achieve parallelism on shared memory ...
This work leverages an original dependency analysis to parallelize loops regardless of their form i...