SynCron：对近数据处理体系结构的有效同步支持
SynCron: Efficient Synchronization Support for Near-Data-Processing Architectures
摘要：
近数据处理（NDP）架构提出了一种很有前途的方式来减轻数据移动成本，并可以提供显着的性能和能源效益的并行应用程序。通常，NDP架构支持若干NDP单元，每个单元包括靠近存储器放置的多个简单核。为了充分利用NDP的优势并实现并行工作负载的高性能，系统的NDP核心之间的高效同步是必要的。然而，在许多NDP系统中支持同步是具有挑战性的，因为它们缺乏通常用于多核系统中的同步的共享高速缓存和硬件缓存一致性支持，并且跨不同NDP单元的通信可能是昂贵的。本文全面研究了NDP系统中的同步问题，并提出了一种端到端的NDP系统同步解决方案SynCron。Syncron在内存附近添加了低成本硬件支持，以实现同步加速，并避免了对硬件缓存一致性支持的需求。SynCron有三个组件：1）专用高速缓冲存储器结构，以避免用于同步的存储器访问并最小化等待时间开销，2）分层消息传递通信协议，以最小化跨系统的NDP单元的昂贵通信，以及3）仅硬件溢出管理方案，以避免当超过用于同步跟踪的硬件资源时的性能降级。我们使用各种并行工作负载评估Syncron，涵盖各种争用场景。与最先进的方法相比，SynCron在高争用情形下将性能平均提高1.27 $\times$（最高可达1.78 $\times$），在低争用实际应用程序下将性能平均提高1.35 $\times$（最高可达2.29 $\times$）。Syncron平均可将系统能耗降低2.08 $\times$（最高可降低4.25 $\times$）。
英文摘要：
Near-Data-Processing (NDP) architectures present a promising way to alleviate data movement costs and can provide significant performance and energy benefits to parallel applications. Typically, NDP architectures support several NDP units, each including multiple simple cores placed close to memory. To fully leverage the benefits of NDP and achieve high performance for parallel workloads, efficient synchronization among the NDP cores of a system is necessary. However, supporting synchronization in many NDP systems is challenging because they lack shared caches and hardware cache coherence support, which are commonly used for synchronization in multicore systems, and communication across different NDP units can be expensive. This paper comprehensively examines the synchronization problem in NDP systems, and proposes SynCron, an end-to-end synchronization solution for NDP systems. SynCron adds low-cost hardware support near memory for synchronization acceleration, and avoids the need for hardware cache coherence support. SynCron has three components: 1) a specialized cache memory structure to avoid memory accesses for synchronization and minimize latency overheads, 2) a hierarchical message-passing communication protocol to minimize expensive communication across NDP units of the system, and 3) a hardware-only overflow management scheme to avoid performance degradation when hardware resources for synchronization tracking are exceeded. We evaluate SynCron using a variety of parallel workloads, covering various contention scenarios. SynCron improves performance by 1.27$\times$ on average (up to 1.78$\times$) under high-contention scenarios, and by 1.35$\times$ on average (up to 2.29$\times$) under low-contention real applications, compared to state-of-the-art approaches. SynCron reduces system energy consumption by 2.08$\times$ on average (up to 4.25$\times$).
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