IntroductionTraditionally, operations with memory on other nodes (remote memory) in cluster environments interconnected with technologies like Gigabit Ethernet have been expensive with latencies several magnitudes slower than local memory accesses. Modern RDMA capable networks such as InfiniBand and Quadrics provide low latency of a few microseconds and high bandwidth of up to 10 Gbps. This has significantly reduced the latency gap between access to local memory and remote memory in modern clusters. Remote idle memory can be exploited to reduce the memory pressure on individual nodes. This is akin to adding an additional level in the memory hierarchy between local memory and the disk, with potentially dramatic performance improvements especially for memory intensive applications. In this paper, we take on the challenge to design a remote paging system for remote memory utilization in InfiniBand clusters. We present the design and implementation of a high performance networking block device (HPBD) over InfiniBandfabric, which serves as a swap device ofkernel Virtual Memory (VM) systemfor efficientpage transfer to/from remote memory servers. Our experiments show that using HPBD, quick sort performs only 1.45 times slower than local memory system, and up to 21 times faster than local disk. And our design is completely transparent to user applications. To the best ofour knowledge, it is thefirst work of a remote pager design using InfiniBandfor remote memory utilization.
An antenna array application with high directivity and low sidelobe level (SLL) is an important technology that can enhance the reliability and validity of a communication system. In recent years, swarm intelligence optimisation algorithms have been widely used in the design of antenna arrays. In this study, a hybrid heuristic swarm intelligence optimisation algorithm called cuckoo search–chicken swarm optimisation (CSCSO) is proposed to optimise the excitation amplitude of a linear antenna array (LAA) and the excitation amplitude and spacing between the array elements of a circular antenna array (CAA). The maximum SLL will be obtained while the mainlobe width is fixed. CSCSO combines cuckoo search (CS) and chicken swarm optimisation (CSO) and thus, it will have the excellent global search capability of CS as well as introduce the hierarchy mechanism of CSO to improve algorithm precision. Chaos theory is utilised to determine the initial solution of the algorithm, while Levy flight weight coefficient is used to improve the convergence rate in CSCSO. Simulation results show that CSCSO has a better performance in terms of solution accuracy and convergence rate in the radiation pattern optimisation of LAA and CAA compared with the standard CSO, CS, and particle swarm optimisation algorithms.
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