MultiLayer processing - an execution model for parallel stateful packet processing

Javier Verdú, M. Nemirovsky, M. Valero
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引用次数: 18

Abstract

Mostly emerging network applications comprise deep packet inspection and/or stateful capabilities. Stateful workloads present limitations that reduce the exploitation of parallelism, unlike other network applications that show marginal dependencies among packets. In addition, differences among packet processing lead to significant negative interaction between threads, especially in the memory hierarchy. We propose MultiLayer Processing (MLP) as an execution model to properly exploit the levels of parallelism of stateful applications. The goal of MLP is to increase the system throughput by increasing the synergy among threads in the memory hierarchy, and alleviating the contention in critical sections of parallel workloads. We show that MLP presents about 2.4x higher throughput than other execution models with large processor architectures.
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多层处理——并行状态包处理的执行模型
大多数新兴的网络应用程序包括深度数据包检测和/或有状态功能。有状态工作负载存在限制,减少了对并行性的利用,不像其他网络应用程序显示数据包之间的边际依赖关系。此外,包处理之间的差异导致线程之间显著的负面交互,特别是在内存层次结构中。我们提出多层处理(MultiLayer Processing, MLP)作为一种执行模型,以适当地利用有状态应用程序的并行度。MLP的目标是通过增加内存层次结构中线程之间的协同作用来提高系统吞吐量,并减轻并行工作负载的关键部分中的争用。我们表明,MLP的吞吐量比具有大型处理器架构的其他执行模型高2.4倍。
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