We investigate an acceleration technique for restarted Krylov subspace methods for computing the action of a function of a large sparse matrix on a vector. Its effect is to ultimately deflate a specific invariant subspace of the matrix which most impedes the convergence of the restarted approximation process. An approximation to the subspace to be deflated is successively refined in the course ...

Following some previous studies on list automata and restarting automata, we introduce a generalized and refined model – the h-lexicalized restarting list automaton (LxRLAW). We argue that this model is useful for expressing transparent variants of lexicalized syntactic analysis, and analysis by reduction in computational linguistics. We present several subclasses of LxRLAW and provide some var...

To satisfy the ever increasing demand for computational resources, high performance computing systems are becoming larger and larger. Unfortunately, the tools supporting system management tasks are only slowly adapting to the increase in components in computational clusters. Virtualization provides concepts which make system management tasks easier to implement by providing more flexibility for...

A deflated restarted Lanczos algorithm is given for both solving symmetric linear equations and computing eigenvalues and eigenvectors. The restarting limits the storage so that finding eigenvectors is practical. Meanwhile, the deflating from the presence of the eigenvectors allows the linear equations to generally have good convergence in spite of the restarting. Some reorthogonalization is ne...

We introduce two new models of two-dimensional computing devices called sgraffito automaton and restarting tiling automaton. The models fulfill two conditions. Firstly, they do not exceed the power of finite-state automata when working over one-dimensional inputs. And secondly, they allow a clear design of important computations. We study properties of the induced families of picture languages....

Clearing and subword-clearing restarting automata are linguistically motivated models of automata. We investigate the problem of grammatical inference for such automata based on the given set of positive and negative samples. We show that it is possible to identify these models in the limit. In this way we can learn a large class of languages. On the other hand, we prove that the task of findin...

It is known that cooperating distributed systems (CD-systems) of stateless deterministic restarting automata with window size 1 accept a class of semi-linear languages that properly includes all rational trace languages. Although the component automata of such a CD-system are all deterministic, the CD-system itself is not, as in each of its computations, the initial component and the successor ...

We consider the optimal control of an unreliable manufacturing system with restarting costs. In 1986 and 1988, Akella and Kumar (for the in nite horizon discounted cost) and Bielecki and Kumar (for the in nite horizon average expected cost) show that the optimal policy is given by an optimal inventory level (“hedging point policy”). Inspired by these simple systems, we explore a new class of mo...