ReOPN: Retargetable Statistical Optimisation and Parallelisation for Network Processors

网络处理器是特定于应用程序的设备，经过优化以尽可能快的速度支持网络协议。对性能、成本和能耗的严格限制导致了异构多核架构的发展，这些架构具有特定于领域的指令集扩展和特定于应用程序的处理元素。然而，这种适应对这些设备的可编程性有很大的影响，并使软件开发成为一项耗时且昂贵的任务。该项目研究了新的统计方法，用于网络处理器的可重目标和自适应编译器定向优化和并行化，以克服由网络协议和应用程序快速增加的复杂性引起的迫在眉睫的软件开发危机。这项研究将使高级编程语言的高效实现，并在高成本和性能敏感的嵌入式计算领域提高程序员的生产力。

Network processors are application specific devices optimised to support network protocols at the highest possible speed. Tight constraints on performance, cost, and energy consumption have led to the development of heterogeneous multi-core architectures with domain specific instruction set extensions and application specific processing elements. However, this adaptation has a strong impact on the programmability of these devices and makes software development a time-consuming and expensive task. This project investigates novel statistical approaches to retargetable and adaptive compiler directed optimisation and parallelisation for network processors to conquer a looming software development crisis caused by the rapidly increasing complexity of network protocols and applications. This research will enable the efficient implementation of high-level programming languages and increase programmer productivity in a highly cost and performance sensitive embedded computing domain.