5,424 research outputs found
The resilience of interdependent transportation networks under targeted attack
Modern world builds on the resilience of interdependent infrastructures
characterized as complex networks. Recently, a framework for analysis of
interdependent networks has been developed to explain the mechanism of
resilience in interdependent networks. Here we extend this interdependent
network model by considering flows in the networks and study the system's
resilience under different attack strategies. In our model, nodes may fail due
to either overload or loss of interdependency. Under the interaction between
these two failure mechanisms, it is shown that interdependent scale-free
networks show extreme vulnerability. The resilience of interdependent SF
networks is found in our simulation much smaller than single SF network or
interdependent SF networks without flows.Comment: 5 pages, 4 figure
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Parallelization and I/O performance optimization of a global nonhydrostatic dynamical core using MPI
The Global ‐ Regional Integrated forecast SysTem (GRIST) is the next-
generation weather and climate integrated model dynamic framework developed by
Chinese Academy of Meteorological Sciences. In this paper, we present several changes
made to the global nonhydrostatic dynamical (GND) core, which is part of the ongoing
prototype of GRIST. The changes leveraging MPI and PnetCDF techniques were targeted
at the parallelization and performance optimization to the original serial GND core.
Meanwhile, some sophisticated data structures and interfaces were designed to adjust
flexibly the size of boundary and halo domains according to the variable accuracy in
parallel context. In addition, the I/O performance of PnetCDF decreases as the number of
MPI processes increases in our experimental environment. Especially when the number
exceeds 6000, it caused system-wide outages (SWO). Thus, a grouping solution was
proposed to overcome that issue. Several experiments were carried out on the
supercomputing platform based on Intel x86 CPUs in the National Supercomputing
Center in Wuxi. The results demonstrated that the parallel GND core based on grouping
solution achieves good strong scalability and improves the performance significantly, as
well as avoiding the SWOs
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