Parallel projection algorithm for solving economics systems

Linear systems are used to analyze situations in which quantitative data is unknown or had to be measured and qualitative information is known; situations that arise frequently in disciplines like economics, biology, etc. The development of new examples in economic is mathematically formalized in linear systems (these systems usually contains a lot of data, so we obtain large linear systems). The most recent mathematical developments about linear systems and their applications in the economics are studied. Many of the iterative methods that are used to solve large linear systems include projection algorithms. Iterative algorithms that represent methods of extracting the solution approximation from a subspace are more and more used to solve large linear systems because they obtain an acceptable solution and the parallelization techniques of the iterative methods can be applied. The task that must be accomplished by the iterative algorithm can be effectively partitioned and distributed to a number of parallel processing elements with shared memories. The paper present a discussion on the parallel simulation of the (CQ) algorithm used to solve large linear systems. It is described the architecture of the application and how it can be successful applied to solve economic systems. Numerical simulations permitted to develop new theories or to incorporate classic theories in theories of a higher level. Some experiments were performed in order to study the algorithm application and to analyze the results that are obtained with the iterative method.