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DTSTAMP:20260705T204753Z
UID:07413133-5933-46ef-8680-855360c2e4cb
DTSTART:20180423T070000Z
DTEND:20180425T143000Z
DESCRIPTION:GPU-accelerated computing drives current scientific research. W
 riting fast numeric algorithms for GPUs offers high application performanc
 e by offloading compute-intensive portions of the code to an NVIDIA GPU. T
 he course will cover basic aspects of GPU architectures and programming. F
 ocus is on the usage of the parallel programming language CUDA-C which all
 ows maximum control of NVIDIA GPU hardware. Examples of increasing complex
 ity will be used to demonstrate optimization and tuning of scientific appl
 ications.\n\nTopics covered will include:\n\nIntroduction to GPU/Parallel 
 computing\n	Programming model CUDA\n	GPU libraries like CuBLAS and CuFFT\n
 	Tools for debugging and profiling\n	Performance optimizations\nPrerequisi
 tes: Some knowledge about Linux\, e.g. make\, command line editor\, Linux 
 shell\, experience in C/C++\n\nApplication \nRegistrations are only consid
 ered until 31 March 2018 due to available space\, the maximal number of pa
 rticipants is limited. Applicants will be notified\, whether they are acce
 pted for participitation.\n\nInstructors: Dr. Jan Meinke\, Jochen Kreutz\,
  Dr. Andreas Herten\, JSC\; Jiri Kraus\, NVIDIA\n\nContact \nFor any quest
 ions concerning the course please send an e-mail to j.meinke@fz-juelich.de
 \n\nhttps://events.prace-ri.eu/event/705/
SUMMARY:GPU Programming with CUDA @ JSC
URL;VALUE=URI:https://events.prace-ri.eu/event/705/
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