InParS: an experimental intelligent parallelization system

In this paper we discuss the design and implementation of an intelligent program parallelization system, called InParS. This system in based on intelligent parallelization models proposed by many researchers in the area of parallelizing compilers. The presented experiment is one of few attempts toward investigating the viability of artificial intelligence techniques in automatic program parallelization. The early version of InParS was aimed at transforming Fortran-like DO loops into a vector code well-suited for vector processors. The new version of InParS targets distributed memory parallel computers. Some preliminary research results are also presented, which give an indication of how incorporating artificial intelligence techniques can contribute towards the success of automatic program parallelization

Generalized methods for algorithm development on optical systems

Abstract A number of recent studies have revealed that the Optical Transpose Interconnection Systems (or OTIS) are promising candidates for future high-performance parallel computers. In this paper, we present and evaluate two general methods for algorithm development on the OTIS. The proposed methods are general in the sense that no specific factor network or problem domain is assumed. The proposed methods allow efficient mapping of a wide class of algorithms into the OTIS. These methods are based on grids and pipelines as popular structures that support a vast body of parallel applications including linear algebra, divide-and-conquer type of algorithms, sorting, and FFT computation. Timing models for measuring the performance of the proposed methods are also provided. Through these models, the performance of various algorithms on the OTIS are evaluated and compared with their counterparts on conventional electronic interconnection systems. This study confirms the viability of the OTIS as an attractive alternative for large-scale parallel architectures. Finally, we show how the proposed methods can be used to design parallel algorithms for linear algebra on the OTIS