Run-time parallelization is a technique for solving problems whose data access patterns are diicult to analyze at compile time. In this paper we propose a worker-checker framework to classify existing run-time parallelization schemes. From the framework, several new approaches to run-time parallelization can be identiied. The implementation of one such scheme, called the overlapped worker-then-...

The development of a computational cost model of parallel batch pattern back propagation training algorithm of a multilayer perceptron is presented in this paper. The model is developed using Bulk Synchronous Parallelism approach. The concrete parameters of the computational cost model are obtained. The developed model is used for the theoretical prediction of a parallelization efficiency of th...

This paper presents a new parallelization method for an ef-cient implementation of unstructured array reductions on shared memory parallel machines with OpenMP. This method is strongly related to parallelization techniques for irregular reductions on distributed memory machines as employed in the context of High Performance Fortran. By exploiting data locality, synchronization is minimized with...

This paper presents a new parallelization method for an efcient implementation of unstructured array reductions on shared memory parallel machines with OpenMP. This method is strongly related to parallelization techniques for irregular reductions on distributed memory machines as employed in the context of High Performance Fortran. By exploiting data locality, synchronization is minimized witho...

This article deals with automatic parallelization of static control programs. During the parallelization process the removal of memory related dependences is usually performed by translating the original program into single assignment form. This total data expansion has a very high memory cost. We present a technique of partial data expansion which leaves untouched the performances of the paral...

This paper parallelizes the spatial pyramid match kernel (SPK) implementation. SPK is one of the most usable kernel methods, along with support vector machine classifier, with high accuracy in object recognition. MATLAB parallel computing toolbox has been used to parallelize SPK. In this implementation, MATLAB Message Passing Interface (MPI) functions and features included in the toolbox help u...

There are two intertwined factors that affect performance of concurrent data structures: the ability of processes to access the data in parallel and the cost of synchronization. It has been observed that for a large class of “concurrency-unfriendly” data structures, fine-grained parallelization does not pay off: an implementation based on a single global lock outperforms fine-grained solutions....