This paper presents a new parallelization method for reductions of arrays with subscripted subscripts on scalable shared-memory multiprocessors. The mapping of computations is based on the conflict-free write distribution of the reduction vector across the processors. The proposed method is general, scalable, and easy to implement on a compiler. A performance evaluation and comparison with other existing techniques is presented. From the experimental results, the proposed method is a clear alternative to the array expansion and privatized buffer methods, usual on state-of-the-art parallelizing compilers, like Polaris or SUIF
Parallelizing compilers for shared-memory multiprocessors typically generate fork/join programs in w...
We detail an algorithm implemented in the R-Stream com-piler1 to perform controlled array expansion ...
In a sequential program, data are often structured in a way that is optimized for a sequential execu...
Different parallelization methods for irregular reductions on shared memory multiprocessors have bee...
This paper presents a new parallelization method for an efficient implementation of unstructured arr...
Proper distribution of operations among parallel processors in a large scientific computation execut...
Reduction recognition and optimization are crucial techniques in parallelizing compilers. They are u...
Reductions are important and time-consuming opera-tions in many scientific codes. Effective parallel...
Abstract: Irregular reduction operations are the core of many large scientific and engineering appli...
Reductions are important and time-consuming operations in many scientific codes. Effective paralleli...
Consider a network of processor elements arranged in a d-dimensional grid, where each processor can ...
Modern computers will increasingly rely on parallelism to achieve high computation rates. Techniques...
Abstract. An algorithm for the distributed computation of sux arrays for large texts is presen-ted. ...
[[abstract]]In distributed memory multicomputers, local memory accesses are much faster than those i...
Two approaches to architecture-independent parallel computation are investigated: a constructive fun...
Parallelizing compilers for shared-memory multiprocessors typically generate fork/join programs in w...
We detail an algorithm implemented in the R-Stream com-piler1 to perform controlled array expansion ...
In a sequential program, data are often structured in a way that is optimized for a sequential execu...
Different parallelization methods for irregular reductions on shared memory multiprocessors have bee...
This paper presents a new parallelization method for an efficient implementation of unstructured arr...
Proper distribution of operations among parallel processors in a large scientific computation execut...
Reduction recognition and optimization are crucial techniques in parallelizing compilers. They are u...
Reductions are important and time-consuming opera-tions in many scientific codes. Effective parallel...
Abstract: Irregular reduction operations are the core of many large scientific and engineering appli...
Reductions are important and time-consuming operations in many scientific codes. Effective paralleli...
Consider a network of processor elements arranged in a d-dimensional grid, where each processor can ...
Modern computers will increasingly rely on parallelism to achieve high computation rates. Techniques...
Abstract. An algorithm for the distributed computation of sux arrays for large texts is presen-ted. ...
[[abstract]]In distributed memory multicomputers, local memory accesses are much faster than those i...
Two approaches to architecture-independent parallel computation are investigated: a constructive fun...
Parallelizing compilers for shared-memory multiprocessors typically generate fork/join programs in w...
We detail an algorithm implemented in the R-Stream com-piler1 to perform controlled array expansion ...
In a sequential program, data are often structured in a way that is optimized for a sequential execu...