Home > Publications database > GPU Programming Part 1: Foundations > print

001     1019123
005     20250822121411.0
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100 1 _ |a Herten, Andreas
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111 2 _ |a JSC - as part of the Training Programme of Forschungszentrum Jülich
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245 _ _ |a GPU Programming Part 1: Foundations
260 _ _ |c 2023
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520 _ _ |a GPU-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.For the first time, the GPU Programming with CUDA course is held in two parts. This course is a basic course covering the foundations of GPU programming including an introduction to GPU/parallel computing, programming with CUDA, GPU libraries, tools for debugging and profiling, and performance optimizations.An advanced course with more involved and specific topics is available as an individual entry.
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700 1 _ |a Meinke, Jan
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700 1 _ |a Haghighi Mood, Kaveh
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700 1 _ |a Kraus, Jiri
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700 1 _ |a Hrywniak, Markus
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856 4 _ |u https://indico3-jsc.fz-juelich.de/event/86/
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