Malleability Techniques Applications in High-Performance Computing

The current static usage model of HPC systems is becoming increasingly inefficient. As a consequence, we see a rise in research on malleable systems, middleware software and applications, which can adjust resources usage dynamically in order to extract a maximum of efficiency. Of particular concern is the emerging class of data-intensive applications and their interaction with classic simulation workloads, driven by the growing need to process extremely large data sets, where uncoordinated file access in combination with limited bandwidth make the I/O system a serious bottleneck. Emerging multi-tier architectures and storage hierarchies and malleability would allow systems to dynamically adjust the computation and storage needs of applications, on the one side, and the global system on the other. Such malleable systems, however, face a series of fundamental research challenges, including control of changes, resource scheduling for optimal usage, applications adaptation to dynamically changing resources, redistribution of data, determining suitability for applications, etc. In order to address these challenges, the HPCMALL workshop will bring together researchers from diverse areas of HPC that are impacted or actively pursuing malleability concepts, from application developers to system architects, from programming model to system software researchers.

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Organizers:

• Estela Suarez (Jülich Supercomputing Centre)
• Martin Schulz (Technical University of Munich)