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PL
Zrealizowano implementację algorytmiczną modelu symulującego funkcjonowanie dwóch elementów systemu elektroenergetycznego korzystając z kart graficznych (GPU, Graphics Processing Unit) działających w środowisku wykonawczym C++ AMP (Accelerated Massive Parallelism). Umożliwiło to zwiększenie wydajności obliczeniowej dzięki równoległemu wykorzystaniu kilkuset rdzeni GPU w porównaniu do wykorzystania kilku rdzeni centralnej jednostki obliczeniowej (CPU, Central Processing Unit). Podano wyniki testowania modelu symulacyjnego.
EN
An algorithmic simulation model of operation for two elements of a power system with the usage of the graphics processing unit (GPU) based on the C++ AMP is implemented. It allows to increase the performance of calculations by the parallel use of several hundred GPU cores compared with several cores of central processing unit (CPU). The test results for the simulation model are presented.
EN
The understanding of the structural and dynamic complexity of neural networks is greatly facilitated by computer simulations. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper a framework for modeling and parallel simulation of biological-inspired large scale spiking neural networks on high-performance graphics processors is described. This tool is implemented in the OpenCL programming technology. It enables simulation study with three models: Integrate-andfire, Hodgkin-Huxley and Izhikevich neuron model. The results of extensive simulations are provided to illustrate the operation and performance of the presented software framework. The particular attention is focused on the computational speed-up factor.
EN
The considerable computation time of a practical application of sequential algorithms for simulating thermal and flow distribution in fluid flow networked systems (FFNS’s) is the motivating factor to study their parallel implementation. The mathematical model formulated and studied in the paper requires the solution of a set of nonlinear equations, which are solved by the Newton-Raphson method. An object-oriented solver automatically formulates the equations for networks of an arbitrary topology. The hydraulic model that is chosen as a benchmark consists of nodal flows and loop equations. A general decomposition algorithm for analysis of flow and temperature distribution in a FFNS is presented, and results of speedup of its parallel implementation are demonstrated.
PL
Zaproponowano model do symulacji równoległej zadania analizy statycznego przepływu cieczy w sieciach przepływowych. Model sprowadza się do rozwiązania układów równan nieliniowych metodą Newtona-Raphsona. Przedstawiono algorytm dekompozycyjny do analizy rozdysponowania przepływu i temperatur w sieci przepływowej oraz wyniki przyspieszenia jego implementacji równoległej.
4
Content available remote A federated approach to parallel and distributed simulation of complex systems
EN
The paper describes a Java-based framework called ASimJava that can be used to develop parallel and distributed simulators of complex real-life systems. Some important issues associated with the implementation of parallel and distributed simulations are discussed. Two principal paradigms for constructing simulations today are considered. Particular attention is paid to an approach for federating parallel and distributed simulators. We describe the design, performance and applications of the ASimJava framework. Two practical examples, namely, a simple manufacturing system and computer network simulations are provided to illustrate the effectiveness and range of applications of the presented software tool.
EN
The paper addresses issues associated with the application of federations of parallel/distributed simulators to large scale networks simulation. We discuss two principal paradigms for constructing simulations today. Particular attention is paid to an approach for federating parallel/distributed simulators. We describe the design and performance of frame relay network simulator (FR/ASimJava) implemented based on a Java-based library for distributed simulation - ASimJava. Six practical examples - six networks operating under frame relay - are presented to illustrate the operation of the given software tool. The focus is on the efficiency of presented network simulator.
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