This paper purpose is to construct maximally parallel algorithms for solving economy problems that are described by dynamic models. The problems of mathematical modeling of a similar class of problems on parallel cluster-type computing systems are considered. Most conventional algorithms for solving such problems (methods of runs, decomposition of a matrix into two diagonal matrices, doubling, etc.), with several processors, usually work no faster than with a single processor. This is caused by significant computations’ sequence of such algorithms. The developed procedure of numerical and analytical sampling is quite simply generalized to other types of differential equations of mathematical physics. In particular, in stationary problems it is easier to localize features and apply high-order schemes in the smoothness areas.
NUMERICAL AND ANALITICAL SCHEMES OF DISTRIBUTED MODELING OF ECONOMIC SYSTEMS
