International Journal of High Speed Computing

Operation class conflicts degrade the performance of a superscalar machine by reducing the instruction-level parallelism exploitable by the machine. The objective of this research is to study the effect of class conflicts on performance degradation of superscalar systems. Three architectural models, the XPCB, XXPB and X4P2 models, are used in simulation and analysis. Each architectural model is considered with two different instruction issue schemes: the in-order issue scheme and the out-of-order issue scheme. The twenty-four Livermore loops are used to evaluate the performance of these three architectural models with the two different instruction issue schemes. Simulation results show that the performance degradations are 0.229, 0.048 and 0.000 for the XPCB, XXPB and X4P2 models with the in-order issue scheme, and are 0.265, 0.041 and 0.000 with the out-of-order issue scheme.

In this paper, we consider the problem of solving tridiagonal linear systems on distributed-memory multiprocessors. We present a new parallel partition-based tridiagonal solver that is suitable for such parallel computers. As compared with the well representative algorithm-cyclic reduction and its parallel variant-cyclic elimination, our algorithm exploits sufficient high of parallelism throughout without incurring more data traffic.

In this note we describe a set of random number generators for NEC SX-3 Supercomputers. The basic sampling source is a vectorized but portable uniform generator using a lagged Fibonacci series. The package contains a vectorized uniform generator zufall, a vectorized normals generator normalen, and a vectorized Poisson generator fische.

An important part of parallel computations, for any group interested in this field, is the purchase of one of the available machines. This new machine becomes the major platform for the group’s efforts in algorithmic development. This paper is an overview of many of the currently available parallel computers. Its original intent was to help in the review, evaluation phase of a machine purchase. The current machine offerings, Cray Research T3D, Fujitsu AP1000 and VPP500, IBM SP1, Intel Paragon, Kendall Square Research KSR1, nCUBE 2 and 3, NEC Cenju-3, Parsytec GigaCube-2, Performance Computing Industries (Meiko) CS-2, Tera, and Thinking Machines Corporation CM-5 are discussed, with emphasis on the unique features and problems of each particular machine and/or company. In addition to the text numerous tables are included to give a overview of the hardware capabilities, the software available and benchmark performance (where available) of each of the computers.

This paper proposes a simple and efficient parallelizing scheme of the genetic algorithm on distributed-memory multiprocessor that maintains the execution behaviours of sequential genetic algorithm. In this parallelizing scheme, the global population is evenly partitioned into several subpopulations, each of which is assigned to the processor to be evolved in parallel. An interprocessor communication pattern, called AAB (All-To-All Broadcasting), is used at each generation in order to exchange the informations on all individuals evolved in all other processors. It allows the processor to reproduce the individuals in a global sense, in other words, the sequential execution behaviours can be maintained in the parallelized genetic algorithm. This paper shows that the genetic algorithms employing widely used selection schemes such as proportionate selection, ranking selection and tournament selection can be efficiently parallelized on distributed-memory multiprocessor using the proposed parallelizing scheme. Some experimental speedups on AP1000 are also presented to show the usefulness of the proposed parallelizing scheme.