Journal:Informatica
Volume 7, Issue 3 (1996), pp. 361–370
Abstract
The queueing system theory is well developed. Such an important problem as the efficient of customer service in efficiency a multichannel queueing system with different productivity of service channels is well developed, too. Exact formulas are obtained from which the loss probability can be computed (if the input stream of customers distributed as Poisson and service time of the customer is the exponential service time). However, these formulas are very complex. So, in this paper, two theorems are proved, in which upper and lower estimates of the loss probability are presented. These estimates are simple formulas that don't become more complex with the growing number of service channels in the queueing system.
Journal:Informatica
Volume 7, Issue 3 (1996), pp. 349–360
Abstract
In this paper, we present an effective performance driven placement with global routing algorithm for macro cells. Our algorithm uses a hierarchical, divide and conquer, quad-partitioning approach. The quad-partitioning routine uses the Tabu Search technique. Our algorithm uses the concept of proximity of regions to approximate the interconnection delays during the placement process. In addition, our algorithm can handle modules whose positions are fixed or are restricted to a particular subregion on the layout frame. Our experimental results indicate the superiority of our placement method in terms of quality of solution and run time when compared to Lin and Du (1990).
Journal:Informatica
Volume 7, Issue 3 (1996), pp. 337–348
Abstract
In the application of Dantzig–Wolfe decomposition to block-angular linear programming problems with R natural blocks. it is possible to have from 1 to R subproblems structurally while solving all R independent subproblems computationally. Early literature on the topic was inconclusive regarding the relative merits of such formulations. This paper attempts clarification by characterizing the significance of the degree of decomposition as well as presenting extensive empirical results.
Journal:Informatica
Volume 7, Issue 3 (1996), pp. 311–336
Abstract
We consider a possibility of automating the analysis of a computer program realizing the objective function of an extremal problem, and of distributing the calculation of the function value into parallel processes on the basis of results of the analysis. The first problem is to recognize the constituent parts of the function. The next one is to determine their computing times. The third problem is to distribute the calculation of these parts among independent processes. A special language similar to PASCAL has been used to describe the objective function. A new scheduling algorithm, seeking to minimize the maximal finishing time of processing units, was proposed and investigated. Experiments are performed using a computer network.
Journal:Informatica
Volume 7, Issue 3 (1996), pp. 295–310
Abstract
In this paper we consider the problem of solving 3D diffusion problems on distributed memory computers. We present a parallel algorithm that is suitable for the number of processors less or equal 8. The pipelining method is used to enlarge the number of processors till 64. The computational grid decomposition method is proposed for heterogenous clusters of workstations which preserves the load balancing of computers. The numerical results for two clusters of workstations are given.
Journal:Informatica
Volume 7, Issue 3 (1996), pp. 281–294
Abstract
This paper deals with load balancing of parallel algorithms for distributed-memory computers. The parallel versions of BLAS subroutines for matrix-vector product and LU factorization are considered. Two task partitioning algorithms are investigated and speed-ups are calculated. The cases of homogeneous and heterogeneous collections of computers/processors are studied, and special partitioning algorithms for heterogeneous workstation clusters are presented.
Journal:Informatica
Volume 7, Issue 2 (1996), pp. 268–274
Abstract
Multidimensional scaling (MDS) is well known technique for analysis of multidimensional data. The most important part of implementation of MDS is minimization of STRESS function. The convergence rate of known local minimization algorithms of STRESS function is no better than superlinear. The regularization of the minimization problem is proposed which enables the minimization of STRESS by means of the conjugate gradient algorithm with quadratic rate of convergence.
Journal:Informatica
Volume 7, Issue 2 (1996), pp. 255–267
Abstract
Recurrent neural networks of binary stochastic units with a general distribution function are studied using Markov chains theory. Sufficient conditions for ergodicity are established and under some assumptions, the stationary distribution is determined. The relation between fixed points and absorbing states is studied both theoretically and through simulations. For numerical studies the notion of almost absorbing state is introduced.
Journal:Informatica
Volume 7, Issue 2 (1996), pp. 229–254
Abstract
This paper is devoted to the consideration of the evolution of the non-migrating limited panmiction population taking into account the size, sex and age structure, pregnancy and females restoration period after delivery. The unique solvability of this model and the condition for the population to vanishe is obtained.
Journal:Informatica
Volume 7, Issue 2 (1996), pp. 175–228
Abstract
The paper describes the use of adaptive and non-periodic sampling in different fields of System Theory and Control. The review is organized in a very comprehensive way and it presents results of the last thirty years about the problem of signal applications using as main tool adaptive sampling schemes including results is the improvement of the transient behaviors. Also, related results are presented about the use of non-periodic sampling in compensation as an alternative design to the well-known frequency domain methods and about the choice of the sampling points in order to improve the transmission of measuring and/or rounding errors towards the results when studying the properties of dynamic systems such as controllability, observability and identifiability.