In this article, a parallel computer program is implemented, based on Finite Element Method, to speed up the analysis of hollow circular cylinders, made from Functionally Graded Materials (FGMs). FGMs are inhomogeneous materials, which their composition gradually varies over volume. In parallel processing, an algorithm is first divided to independent tasks, which may use individual or shared da...

We study the effect of speedup on the dynamical behavior of a single cyclic bus in a bus system with many bus stops. We present a nonlinear-map model of a cyclic bus to take into account the speedup. When the cyclic bus is delayed, the bus speeds up to retrieve the delay. It is found that the cyclic bus exhibits chaotic motion with increasing speedup. The chaotic motion depends on both speedup ...

Speedup learning is a branch of machine learning that studies learning mechanisms for speeding up problem solvers based on problem solving experience. The input to a speedup learner typically consists of observations of prior problem-solving experience, which may include traces of the problem solver’s operations and/or solutions to solved problems. The output is knowledge that the problem solve...

There seems to be, at least in practice, a fundamental conflict within program transformations. One way: hand transformations can yield dramatic speedups, but seem to require human insight. They are thus are only suited to small programs and have not been successfully automated. On the other hand, there exist a number of well-known automatic program transformations; but these have been proven t...

This paper addresses the problem of inferring extended finite-state machines (EFSMs) with parallel algorithms. We propose a number of parallel versions of a recent EFSM inference algorithm MuACO. Two of the proposed algorithms demonstrate super-linear speedup.