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Next generation in-situ/in-transit data processing has been proposed for addressing data challenges at extreme scales. However, further research is necessary in order to understand how growing data sizes from data intensive simulations coupled with limited DRAM capacity in High End Computing clusters will impact the effectiveness of this approach. In this work, we propose using deep memory levels...
Emerging scientific application workflows are composed of heterogeneous coupled component applications that simulate different aspects of the physical phenomena being modeled, and that interact and exchange significant volumes of data at runtime. With the increasing performance gap between on-chip data sharing and off-chip data transfers in current systems based on multicore processors, moving large...
Scientific applications are striving to accurately simulate multiple interacting physical processes that comprise complex phenomena being modeled. Efficient and scalable parallel implementations of these coupled simulations present challenging interaction and coordination requirements, especially when the coupled physical processes are computationally heterogeneous and progress at different speeds...
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