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Digital neural cell scheduler for ATM switching

机译:用于ATM交换的数字神经元调度程序

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An input buffer-type ATM switch with a window-based contention algorithm is proposed, modeled in VHDL, for a high-speed cell scheduler for ATM switching. A digital Hopfield neural cell scheduler which has the ability of real-time processing is used to solve loss of throughput due to head-of-line (HOL) and internal blocking when FIFO queueing is employed at the banyan network. In this scheduler, consequently, a tag value which has a destination-cell address is changed into a corresponding binary pattern, modified into a non-internal blocking pattern by preprocessing and optimization, which results in the reduction of the work load of the cell scheduler and smoothing of the priority control of the scheduler. By skipping random input operations and reducing the demand on arithmetic operations by operating on a minimized number of bits in this scheduler, it is found that we can minimize the delay for scheduling and maximise the selection of non-blocking cells leading to high performance. We use a performance metrix, evaluating its performance in an average number of clock cycles needed for scheduling a cell from the queue to the banyan network.
机译:提出了一种基于窗口竞争算法的输入缓冲区型ATM交换机,该模型以VHDL建模,用于ATM交换的高速信元调度器。当在榕树网络中使用FIFO排队时,具有实时处理能力的数字Hopfield神经元调度程序用于解决由于行头(HOL)和内部阻塞而导致的吞吐量损失。因此,在该调度器中,具有目的地单元地址的标签值被改变为对应的二进制模式,通过预处理和优化而被修改为非内部阻塞模式,从而降低了单元调度器的工作量。并优化调度程序的优先级控制。通过跳过随机输入操作并通过在此调度程序中以最小数量的位进行操作来减少对算术运算的需求,我们发现我们可以最小化调度的延迟,并最大化导致性能的非阻塞单元的选择。我们使用性能指标,以将单元从队列调度到榕树网络所需的平均时钟周期数来评估其性能。

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