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001019178 1001_ $$0P:(DE-Juel1)132189$$aMeinke, Jan$$b0$$ufzj
001019178 1112_ $$aJSC - as part of the Training Programme of Forschungszentrum Jülich$$conline$$d2023-06-19 - 2023-06-23$$wGermany
001019178 245__ $$aGPU Programming Part 2: Advanced GPU Programming
001019178 260__ $$c2023
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001019178 500__ $$aSee https://juser.fz-juelich.de/record/1019123 for the JuSER entry for the Basic Course.
001019178 520__ $$aGPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GPUs offers high application performance by offloading compute-intensive portions of the code to a GPU.The course covers aspects of GPU architectures and programming. Focus is on the usage of the parallel programming language CUDA C++, which allows maximum control of NVIDIA GPU hardware. Examples of increasing complexity are used to demonstrate optimization and tuning of scientific applications. The foundations of GPU programming are covered in another dedicated Basic Course.This advanced course consists of modules providing more in-depth coverage of multi-GPU programming, modern CUDA concepts, CUDA Fortran, and portable programming models such as OpenACC and C++ parallel STL algorithms.
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001019178 536__ $$0G:(DE-HGF)POF4-5122$$a5122 - Future Computing & Big Data Systems (POF4-512)$$cPOF4-512$$fPOF IV$$x2
001019178 536__ $$0G:(DE-Juel-1)ATML-X-DEV$$aATML-X-DEV - ATML Accelerating Devices (ATML-X-DEV)$$cATML-X-DEV$$x3
001019178 7001_ $$0P:(DE-Juel1)145478$$aHerten, Andreas$$b1$$eCorresponding author$$ufzj
001019178 7001_ $$0P:(DE-Juel1)180799$$aHrywniak, Markus$$b2$$ufzj
001019178 7001_ $$0P:(DE-Juel1)137023$$aKraus, Jiri$$b3$$ufzj
001019178 7001_ $$0P:(DE-Juel1)176293$$aHaghighi Mood, Kaveh$$b4$$ufzj
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