In recent years, the demand for high-performance computing in various disciplines of ICTs has affected the dependency on single core processes due to its decline in efficiency. Whereas, this requirement of advance in ...
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The grid connection of a mass of distributed power sources in the AC/DC hybrid micro-grid will cause harmonics, voltage sags, voltage fluctuations, and flicker in the grid, which seriously affects the power quality of...
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parallel discrete event simulation is a fundamental simulation technology that is essential to the parallelization of event-based models including hardware and transportation systems. parallelization is often difficul...
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ISBN:
(纸本)9798400703638
parallel discrete event simulation is a fundamental simulation technology that is essential to the parallelization of event-based models including hardware and transportation systems. parallelization is often difficult due to dynamic data-dependencies and limited computational work for hiding runtime overheads. We present Devastator, a scalable parallel discrete event simulation framework for modern C++. Devastator provides a productive API that leverages C++'s type system to eliminate boilerplate code. Devastator has been designed to specifically optimize performance on distributed many-core architectures with deepening memory hierarchies. Devastator relies on the GASNet-Ex communication runtime as well as lock-free message queues to achieve highly competitive performance. We perform strong and weak scaling studies on NERSC's Perlmutter up to 32,698 cores and demonstrate an up to 5x speed-up over the ROSS simulator for workloads with substantial locality.
Electric vehicles (EVs) are a major solution for sustainability challenges such as global warming, fossil fuel depletion, emission of greenhouse gas that require immediate attention. Electric vehicles will be required...
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To improve the task scheduling efficiency in computing power networks, this paper proposes a global task scheduling method based on network measurement and prediction in computing power networks (GTS-MP), which select...
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In modern society, power communication networks play a crucial role, and their stable operation is essential for the safety and efficiency of power grids. In this paper, a distributed simulation system for power commu...
Users may access virtual, scalable, and dynamic resources using cloud computing, which is a novel technology that charges them only for the resources they use. This technology is reliant on a network to function. Seve...
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ISBN:
(纸本)9781665411202
Users may access virtual, scalable, and dynamic resources using cloud computing, which is a novel technology that charges them only for the resources they use. This technology is reliant on a network to function. Several services, like as e-commerce apps, use the whole network as a result of the sheer scope of the network. Cloud computing has progressed through three phases in terms of practical development: distributedcomputing, parallelcomputing, and gridcomputing. Cloud computing is a cutting-edge technology that installs networks of computers, many of which are situated in faraway locations, to conduct operations on massive amounts of data in real time, main challenge in cloud workflow Scheduling in edge context. In proposed approach we used hybrid approach using Tabu and Grey Wolf Optimization. In experiment improved results of approx. 5-10% average in all performance metrics are obtained.
Due to the influence of distributed power supply access in islanded microgrid, the error of direct power flow calculation is large. Therefore, a power flow calculation method for islanded microgrid based on graph para...
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作者：
Zhang, LupingZhang, ZhimengEast China Univ Technol
Jiangxi Engn Technol Res Ctr Nucl Geosci Data Sci Sch Informat Engn Jiangxi Engn Lab Radioact Geosci & Big Data Techn Nanchang 330013 Jiangxi Peoples R China
Membrane computing provides efficient computing devices for broad applications due to its distributed storage and the parallel processing. As computing devices in membrane computing, numerical P systems with threshold...
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ISBN:
(纸本)9789819722716;9789819722723
Membrane computing provides efficient computing devices for broad applications due to its distributed storage and the parallel processing. As computing devices in membrane computing, numerical P systems with thresholds (NPT systems) are proven to be Turing universal, and their computational and operational semantics need to be further investigated. In this work, the intrinsic relationship between NPT systems and Petri nets is concerned. The ingredients of Petri nets are associated with the elements of numerical variables in NPT systems, and the operations of Petri nets are associated with the evolutions of NPT systems. The results on the boundedness and reachability of NPT systems are obtained by using the relationship between NPT systems and Petri nets.
In the exascale computing era, optimizing MPI collective performance in high-performance computing (HPC) applications is critical. Current algorithms face performance degradation due to system call overhead, page faul...
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ISBN:
(纸本)9798400701559
In the exascale computing era, optimizing MPI collective performance in high-performance computing (HPC) applications is critical. Current algorithms face performance degradation due to system call overhead, page faults, or data-copy latency, affecting HPC applications' efficiency and scalability. To address these issues, we propose PiP-MColl, a Process-in-Process-based Multi-object Interprocess MPI Collective design that maximizes small message MPI collective performance at scale. PiP-MColl features efficient multiple sender and receiver collective algorithms and leverages Process-in-Process shared memory techniques to eliminate unnecessary system call, page fault overhead, and extra data copy, improving intra- and inter-node message rate and throughput. Our design also boosts performance for larger messages, resulting in comprehensive improvement for various message sizes. Experimental results show that PiP-MColl outperforms popular MPI libraries, including OpenMPI, MVAPICH2, and Intel MPI, by up to 4.6X for MPI collectives like MPI_Scatter and MPI_Allgather.
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