Karl Fürlinger

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1 Jülich Supercomputing Centre, Forschungszentrum Jülich, Germany {f.wolf, e.abraham, d.becker, w.frings, m.geimer, m.a.hermanns, b.mohr, m.pfeifer, z.szebenyi, b.wylie}@fz-juelich.de 2 Department of Computer Science and Aachen Institute for Advanced Study in Computational Engineering Science, RWTH Aachen University, Germany 3 Innovative Computing(More)
As supercomputers are being built from an ever increasing number of processing elements, the effort required to achieve a substantial fraction of the system peak performance is continuously growing. Tools are needed that give developers and computing center staff holistic indicators about the resource consumption of applications and potential performance(More)
DASH is a realization of the PGAS (partitioned global address space) model in the form of a C++ template library. Operator overloading is used to provide global-view PGAS semantics without the need for a custom PGAS (pre-)compiler. The DASH library is implemented on top of our runtime system DART, which provides an abstraction layer on top of existing(More)
In the last two decades supercomputers have sustained a remarkable growth in performance that even out-performed the predictions of Moore’s law, primarily due to increased levels of parallelism [19]. As industry and academia try to come up with viable approaches for exascale systems, attention turns to energy efficiency as the primary design consideration.(More)
We present a detailed investigation of the scalability characteristics of the SPEC OpenMP benchmarks on large-scale shared memory multiprocessor machines. Our study is based on a tool that quantifies four well-defined overhead classes that can limit scalability – for each parallel region separately and for the application as a whole.
A high-level understanding of how an application executes and which performance characteristics it exhibits is essential in many areas of high performance computing, such as application optimization, hardware development, and system procurement. Tools are needed to help users in uncovering the application characteristics, but current approaches are(More)
Analyzing the scalability behavior and the overheads of OpenMP applications is an important step in the development process of scientific software. Unfortunately, few tools are available that allow an exact quantification of OpenMP related overheads and scalability characteristics. We present a methodology in which we define four overhead categories that we(More)