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Moderne CPU-Architekturen erfordern die Verwendung von Vektorinstruktionen, um die vorhandene Leistung vollständig auszuschöpfen. Aktuelle Compiler bieten Möglichkeiten zur automatischen Vektorisierung von Programmcode. Im Rahmen dieser Arbeit werden an Testfällen verschiedene Compiler auf ihre Fähigkeiten zur Autovektorisierung getestet und evaluiert, um Stärken und Schwächen der jeweiligen Compiler aufzuzeigen. Es werden Laufzeitergebnisse und Vektorisierungsvermögen miteinander verglichen und eine Empfehlung in Abhängigkeit des jeweiligen Anwendungsfalls gegeben.
Computers, servers and supercomputers with more than one GPU become more and more common. To fully utilize such systems the application needs to be aware of the additional GPUs. E.g., computational workload needs to be distributed across the GPUs. Along with that goes data movement as well as communication. Recently, NVIDIA introduced new features, Unified Memory and Cooperative Groups, that enable programmers to extend their applications with multi-GPU capabilities. In this thesis the aforementioned features are presented in detail and evaluated in the context of the GPU molecular dynamics simulation HAL's MD package on the latest NVIDIA GPU architecture Pascal. A hotspot analysis with the NVIDIA Visual Profiler identified the radix sort as a major hotspot within HAL's MD package. This thesis presents an approach towards a multi-GPU implementation of radix sort. The individual kernels are analysed and an implementation is discussed. Then, the radix sort is transformed into a multi-GPU implementation kernel per kernel. For each step the individual runtime measurements and bottlenecks are presented to analyse the approach. A general sequence diagram of the implementation shows how the individual parts interact with each other. The outlook discusses the further development of HAL's MD package, especially the force computation for multi-GPU which has not been covered in this thesis.