Clustering performance data efficiently at massive scales
Proceedings of the 24th ACM International Conference on Supercomputing
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Exascale systems will provide an unprecedented opportunity for science, one that will make it possible to use computation not only as a critical tool along with theory and experiment in understanding the behavior of the fundamental components of nature, but also for critical advances for the nationâ聙聶s energy needs and security. To create exascale systems and software that will enable the US Department of Energy (DOE) to meet the science goals critical to the nationâ聙聶s energy, ecological sustainability, and global security, we must focus on major architecture, software, algorithm, and data challenges, and build on newly emerging programming environments. Only with this new infrastructure will applications be able to scale up to the required levels of parallelism and integrate technologies into complex coupled systems for real-world multidisciplinary modeling and simulation. Achieving this goal will likely involve a shift from current static approaches for application development and execution to a combination of new software tools, algorithms, and dynamically adaptive methods.