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Search results for: capacity memory simulations

  • Electromagnetic Simulations with 3D FEM and Intel Optane Persistent Memory

    Publication

    - Year 2022

    Abstract—Intel Optane persistent memory has the potential to induce a change in how high-performance calculations requiring a large system memory capacity are conducted. This article presents what this change may look like in the case of factorization of large sparse matrices describing electromagnetic problems arising in the 3D FEM analysis of passive highfrequency components. In numerical tests, the Intel oneAPI MKL PARDISO was...

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  • Intelligent microbearing project with memory of stress-strain history

    Taking into account the increasing need of intelligent micro-bearing with memory, this paper presents the optimization, simulation and practical application of operating parameters(load carrying capacity, friction forces, friction coefficient, wear), simulation for hydrodynamic HDD micro-bearing with curvilinear nano-grooved journal profile. One of the reason of such journal profile is that this journal profile contributes to the...

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  • Sylwester Kaczmarek dr hab. inż.

    Sylwester Kaczmarek received his M.Sc in electronics engineering, Ph.D. and D.Sc. in switching and teletraffic science from the Gdansk University of Technology, Gdansk, Poland, in 1972, 1981 and 1994, respectively. His research interests include: IP QoS and GMPLS and SDN networks, switching, QoS routing, teletraffic, multimedia services and quality of services. Currently, his research is focused on developing and applicability...

  • Simulation of parallel similarity measure computations for large data sets

    The paper presents our approach to implementation of similarity measure for big data analysis in a parallel environment. We describe the algorithm for parallelisation of the computations. We provide results from a real MPI application for computations of similarity measures as well as results achieved with our simulation software. The simulation environment allows us to model parallel systems of various sizes with various components...

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  • An Approximation of the Zero Error Capacity by a Greedy Algorithm.

    Publication

    - Year 2020

    We present a greedy algorithm that determines a lower bound on the zero error capacity. The algorithm has many new advantages, e.g., it does not store a whole product graph in a computer memory and it uses the so-called distributions in all dimensions to get a better approximation of the zero error capacity. We also show an additional application of our algorithm.

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