Abstract
The number of processor cores on modern supercomputers is increasing from generation to generation, and as a consequence HPC applications are required to harness much higher degrees of parallelism to satisfy their growing demand for computing power. However, writing code that runs efficiently on large processor configurations remains a significant challenge. The situation is exacerbated by the rising number of cores imposing scalability demands not only on applications but also on the software tools needed for their development.
To address this challenge, Jülich Supercomputing Centre creates software technologies aimed at improving the performance of applications running on leadership-class systems. At the center of our activities lies the development of Scalasca, a performance-analysis tool that has been specifically designed for large-scale systems and that allows the automatic identification of harmful wait states in applications running on hundreds of thousands of processors. In this article, we review recent developments in the open-source Scalasca toolset, highlight research activities of the Scalasca team during the past two years and give an outlook on future work.
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References
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Geimer, M. et al. (2010). Recent Developments in the Scalasca Toolset. In: Müller, M., Resch, M., Schulz, A., Nagel, W. (eds) Tools for High Performance Computing 2009. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11261-4_4
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DOI: https://doi.org/10.1007/978-3-642-11261-4_4
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