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Pipelined Heap (Priority Queue) Management for Advanced Scheduling in High-Speed Networks

机译:高速网络中高级调度的流水堆(优先级队列)管理

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摘要

Per-flow queueing with sophisticated scheduling is one of the methods for providing advanced quality of service (QoS) guarantees. The hardest and most interesting scheduling algorithms rely on a common computational primitive, implemented via priority queues. To support such scheduling for a large number of flows at OC-192 (10 Gb/s) rates and beyond, pipelined management of the priority queue is needed. Large priority queues can be built using either calendar queues or heap data structures; heaps feature smaller silicon area than calendar queues. We present heap management algorithms that can be gracefully pipelined; they constitute modifications of the traditional ones. We discuss how to use pipelined heap managers in switches and routers and their cost-performance tradeoffs. The design can be configured to any heap size, and, using 2-port 4-wide SRAMs, it can support initiating a new operation on every clock cycle, except that an insert operation or one idle (bubble) cycle is needed between two successive delete operations. We present a pipelined heap manager implemented in synthesizable Verilog form, as a core integratable into ASICs, along with cost and performance analysis information. For a 16 K entry example in 0.13- $mu$m CMOS technology, silicon area is below 10 mm$^2$ (less than 8% of a typical ASIC chip) and performance is a few hundred million operations per second. We have verified our design by simulating it against three heap models of varying abstraction.
机译:具有复杂调度的按流排队是提供高级服务质量(QoS)保证的方法之一。最困难,最有趣的调度算法依赖于通过优先级队列实现的通用计算基元。为了支持以OC-192(10 Gb / s)速率及更高速率进行大量流的此类调度,需要对优先级队列进行流水线管理。可以使用日历队列或堆数据结构来构建大优先级队列。堆比日历队列的硅面积小。我们提出了可以很好地流水线化的堆管理算法。它们构成了传统的修改。我们讨论了如何在交换机和路由器中使用流水线堆管理器以及它们在性价比之间的权衡。该设计可以配置为任何堆大小,并且使用2端口4宽SRAM,它可以支持在每个时钟周期启动一个新操作,不同的是在两个连续的时钟之间需要一个插入操作或一个空闲(气泡)周期删除操作。我们介绍了以可综合Verilog形式实现的流水堆管理器,它是可集成到ASIC中的核心,以及成本和性能分析信息。以0.13微米CMOS技术的16 K入门示例为例,硅面积低于10毫米2英镑(不到典型ASIC芯片的8%),并且性能为每秒几亿次操作。我们已经通过对三个具有不同抽象概念的堆模型进行仿真来验证了我们的设计。

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