100 research outputs found

    ИсслСдованиС напряТСнного состояния Π² струТкС

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    ΠŸΡ€ΠΎΡ„Π΅ΡΡΠΎΡ€Ρƒ А. М. ΠšΠΎΡ€ΠΈΠΊΠΎΠ²Ρƒ - 70 Π»Π΅Ρ‚

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    1 января 2012 Π³. ΠΎΡ‚ΠΌΠ΅Ρ‚ΠΈΠ» юбилСй Π΄ΠΎΠΊΡ‚ΠΎΡ€ тСхничСских Π½Π°ΡƒΠΊ, профСссор, ЗаслуТСнный Π΄Π΅ΡΡ‚Π΅Π»ΡŒ Π½Π°ΡƒΠΊΠΈ Π Π€, ΠŸΠΎΡ‡Π΅Ρ‚Π½Ρ‹ΠΉ Ρ€Π°Π±ΠΎΡ‚Π½ΠΈΠΊ Π²Ρ‹ΡΡˆΠ΅Π³ΠΎ ΠΏΡ€ΠΎΡ„Π΅ΡΡΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ образования Π Π€ ΠΈ ΠŸΠΎΡ‡Π΅Ρ‚Π½Ρ‹ΠΉ Ρ€Π°Π±ΠΎΡ‚Π½ΠΈΠΊ Π½Π°ΡƒΠΊΠΈ ΠΈ Ρ‚Π΅Ρ…Π½ΠΈΠΊΠΈ Π Π€ Анатолий ΠœΠΈΡ…Π°ΠΉΠ»ΠΎΠ²ΠΈΡ‡ ΠšΠΎΡ€ΠΈΠΊΠΎΠ²

    О Π½Π΅ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… направлСниях дальнСйшСй Π°Π²Ρ‚ΠΎΠΌΠ°Ρ‚ΠΈΠ·Π°Ρ†ΠΈΠΈ Π±Π΅Ρ‚Π°Ρ‚Ρ€ΠΎΠ½ΠΎΠ²

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    The novel ScaleMP vSMP architecture employs commodity x86-based servers with an InfiniBand network to assemble a large shared memory system at an attractive price point. We examine this combined hardware- and softwareapproach of a DSM system using both system-level kernel benchmarks as well as real-world application codes. We compare this architecture with traditional shared memory machines and elaborate on strategies to tune application codes parallelized with OpenMP on multiple levels. Finally we summarize the necessary conditions which a scalable application has to fulfill in order to profit from the full potential of the ScaleMP approach

    COMMON MARKETING MISTAKES

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    An efficient parallel algorithm for the computation of parametric sensitivities for differential-algebraic equations (DAEs) with a focus on dynamic optimization problems is presented. A speedup of about 4 can be obtained for process models of more than 13500 DAEs and 75 parameters employing 8 processor cores in parallel using a Windows based system. The algorithm obtains its efficiency by decoupling the sensitivity equations from the state equations of the DAE. Furthermore, the costly Jacobian matrices are computed separately by other processes. The computational effort for a combined state and sensitivity integration can almost be reduced to the computational effort of the pure state integration, which is the theoretical limit of the suggested approach
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