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Seminar Advanced Topics in Parallel Computing 18

Efficient use of high-end supercomputing resources for simulations of a phenomenon from physics, chemistry, biology, financial modelling, neural networks or signal processing, is only possible if the corresponding applications are designed using modern and advanced computational methods in parallel programming. Often the ability of the application to use newest computing hardware like accelerators or high-speed transmission technology, plays a central role for being granted an access to big supercomputers. Furthermore improving existing algorithms of simulation codes by using advanced technique of parallelization can result to crucial advantages for efficiency in time: when simply speeding up the generation of results, or even saving energy: when the optimised application is able to generate the same results through redistribution of main computation into low-energy consuming part of computers like graphical co-processors, local disks, cache, etc. Students attending this seminar will be assigned topics related to up-to-date technology in the field of advanced parallel programming for distributed and shared memory systems, using MPI, OpenMP, CUDA, OpenCL, OpenACC. Also the tools for analysis of scalability, efficiency and potential consumption of time by an application will be studied and topics in parallel file systems, high-speed communications could be investigated. MapReduce on HPC clusters - Apache Spark Fabric Technology Parallel I/O via HDF5 SIMD Programmierung Network Toppology Scheduling algorithm OpenACC - der Programmierstandard für heterogene CPU/GPU Parallelprogrammierung OpenMP 4.0 neuer Standard zur mehrfädigen Programmierung von CPUs & GPUs Parallelisierung rekursiver Programme mit Hilfe des OpenMP Task-Konzept Solving Sodoku with OpenMP Tasks Symmetric Reverse Cuthill-McKee on Multicore or GPUs Monte Carlo Method on GPUs Realize the PageRank Algorithm in OpenMP Parallel Computing with MATLAB

Zusammenfassung

Efficient use of high-end supercomputing resources for simulations of a phenomenon from physics, chemistry, biology, financial modelling, neural networks or signal processing, is only possible if the corresponding applications are designed using modern and advanced computational methods in parallel programming. Often the ability of the application to use newest computing hardware like accelerators or high-speed transmission technology, plays a central role for being granted an access to big supercomputers.

Furthermore improving existing algorithms of simulation codes by using advanced technique of parallelization can result to crucial advantages for efficiency in time: when simply speeding up the generation of results, or even saving energy: when the optimised application is able to generate the same results through redistribution of main computation into low-energy consuming part of computers like graphical co-processors, local disks, cache, etc.

Students attending this seminar will be assigned topics related to up-to-date technology in the field of advanced parallel programming for distributed and shared memory systems, using MPI, OpenMP, CUDA, OpenCL, OpenACC. Also the tools for analysis of scalability, efficiency and potential consumption of time by an application will be studied and topics in parallel file systems, high-speed communications could be investigated.

MapReduce on HPC clusters - Apache Spark
Fabric Technology
Parallel I/O via HDF5
SIMD Programmierung
Network Toppology
Scheduling algorithm
OpenACC - der Programmierstandard für heterogene CPU/GPU Parallelprogrammierung
OpenMP 4.0 neuer Standard zur mehrfädigen Programmierung von CPUs & GPUs
Parallelisierung rekursiver Programme mit Hilfe des OpenMP Task-Konzept
Solving Sodoku with OpenMP Tasks
Symmetric Reverse Cuthill-McKee on Multicore or GPUs
Monte Carlo Method on GPUs
Realize the PageRank Algorithm in OpenMP
Parallel Computing with MATLAB

Allgemein

Sprache
Deutsch

Tutorielle Betreuung

[ay8233]

[az2556]

[pn9734]

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Unbegrenzt – wenn online geschaltet
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Zeitraum für Beitritte
Unbegrenzt
Veranstaltungszeitraum
23. Apr 2018 - 30. Jul 2018

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1099104
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Erstellt am
21. Mär 2018, 10:18