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Server-Based Data Push Architecture for Multi-Processor Environments

机译:用于多处理器环境的基于服务器的数据推送架构

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Data access delay is a major bottleneck in utilizing current high-end computing (HEC) machines. Prefetch-ing, where data is fetched before CPU demands for it, has been considered as an effective solution to masking data access delay. However, current client-initiated prefetching strategies, where a computing processor initiates prefetching instructions, have many limitations. They do not work well for applications with complex, non-contiguous data access patterns. While technology advances continue to increase the gap between computing and data access performance, trading computing power for reducing data access delay has become a natural choice. In this paper, we present a server-based data-push approach and discuss its associated implementation mechanisms. In the server-push architecture, a dedicated server called Data Push Server (DPS) initiates and proactively pushes data closer to the client in time. Issues, such as what data to fetch, when to fetch, and how to push are studied. The SimpleScalar simulator is modified with a dedicated prefetching engine that pushes data for another processor to test DPS based prefetching. Simulation results show that L1 Cache miss rate can be reduced by up to 97% (71% on average) over a superscalar processor for SPEC CPU2000 benchmarks that have high cache miss rates.
机译:数据访问延迟是利用当前高端计算(HEC)机器的主要瓶颈。预取,即在CPU要求数据之前先取数据,已被认为是掩盖数据访问延迟的有效解决方案。但是,当前的客户端启动的预取策略(其中计算处理器启动预取指令)有很多限制。它们不适用于具有复杂,不连续数据访问模式的应用程序。尽管技术的进步继续扩大了计算和数据访问性能之间的差距,但为减少数据访问延迟而交换计算能力已成为一种自然选择。在本文中,我们提出了一种基于服务器的数据推送方法,并讨论了其相关的实现机制。在服务器推送架构中,称为数据推送服务器(DPS)的专用服务器会及时启动并主动将数据推送到客户端附近。研究了诸如要获取哪些数据,何时获取以及如何推送等问题。 SimpleScalar仿真器通过专用的预取引擎进行了修改,该引擎将数据推入另一个处理器以测试基于DPS的预取。仿真结果表明,对于具有较高高速缓存未命中率的SPEC CPU2000基准,与超标量处理器相比,L1高速缓存未命中率可降低多达97%(平均71%)。

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