EXAGRAPH: Graph and combinatorial methods for enabling exascale applications

Models of Computation - Enabling Exascale

The derivation of new systems’ software and tools for high performance computing environments at Exascale will demand realignment and adjustment of functionality and capability of software components to exploit the new opportunities and address the new challenges of future system architectures, which themselves will be created in response to advancing hardware technologies. The evolution of dig...

Stochastic local search methods for highly constrained combinatorial optimisation problems: graph colouring, generalisations, and applications

Resilience for Exascale Enabled Multigrid Methods

With the increasing number of components and further miniaturization the mean time between faults in supercomputers will decrease. System level fault tolerance techniques are expensive and cost energy, since they are often based on redundancy. Also classical check-point-restart techniques reach their limits when the time for storing the system state to backup memory becomes excessive. Therefore...

islanding detection methods for microgrids

امروزه استفاده از منابع انرژی پراکنده کاربرد وسیعی یافته است . اگر چه این منابع بسیاری از مشکلات شبکه را حل می کنند اما زیاد شدن آنها مسائل فراوانی برای سیستم قدرت به همراه دارد . استفاده از میکروشبکه راه حلی است که علاوه بر استفاده از مزایای منابع انرژی پراکنده برخی از مشکلات ایجاد شده توسط آنها را نیز منتفی می کند . همچنین میکروشبکه ها کیفیت برق و قابلیت اطمینان تامین انرژی مشترکان را افزایش ...

Challenges and Recommendations for Preparing HPC Applications for Exascale

In this paper we propose an approach for preparing HPC applications for Exascale. A high-level application model capturing nonfunctional properties combined with an abstract machine model will enable application improvements, and will serve as input to runtime systems to handle performance and energy optimizations, and self-aware fault management. A tunable abstract machine model includes curre...