METRIC SYSTEMS FOR EVALUATING THE EFFICIENCY AND SCALABILITY OF PARALLEL COMPUTING

Abstract

"The current state of development of computer technology allows you to build parallel computer systems that use almost unlimited number of processors. The availability of such systems has aroused interest in studying the performance of parallel computers, which contain a large number of processors, in the implementation of real multidimensional problems. One way to increase the efficiency of parallel architectures is to reduce the time required to perform a time-consuming task, which should be commensurate with the number of processing resources used to solve this problem. The second direction is the development of highly scalable parallel or parallel algorithms. Under the scalability of the parallel algorithm on the parallel architecture we will consider a measure of its ability to efficiently use a growing number of processors. Scalability analysis can be used to select the best combination of algorithm architecture for a problem with different constraints on the size of the problem and the number of processors. It can be used to predict the performance of a parallel algorithm and a parallel architecture for a large number of processors based on known performance on a smaller number of processors. For a fixed size of the problem, it can be used to determine the optimal number of processors, which will be used and the maximum possible acceleration that can be obtained. Scalability analysis can also predict the impact of changes in hardware technology on performance and thus help develop the best parallel architectures to solve different problems The aim of the work is to critically evaluate the state of modern theory of analysis of aircraft performance and scalability and to demonstrate further research on the development of new and more complex analytical tools to analyze the effective use of the benefits of parallel equipment. The main task of the study is to develop new and modify existing theoretical models, methods and formalisms to study the problems of efficiency and scalability of parallel computing. Mathematically, to simplify the analysis, it is assumed that all temporal characteristics are non-negative. This means that acceleration is always limited by the number of processors, p, and efficiency - by one. For example, acceleration can be super-linear, overhead can be negative if memory is hierarchical and access time is increased discretely by increasing the memory used by the program. In this case, the effective computing speed of a large program will be slower on a serial processor than on a parallel computer with similar processors."