利用 CCA 探索面向动态图处理的消息驱动系统设计空间
Exploring the Design Space for Message-Driven Systems for Dynamic Graph Processing using CCA
AI总结：
本文提出非冯·诺依曼的 CCA 架构，利用以内存为中心、消息驱动异步控制和全局命名空间乱序执行等机制，为动态图处理探索下一代高度并行硬件方向。
摘要：
已成功部署用于密集规则工作负载的计算机系统，在应用于不规则且动态的图应用时，无法实现可扩展性和效率。传统计算系统严重依赖静态、规则、数值密集型计算，而执行并行图应用的高性能计算系统几乎没有空间或时间局部性，并且具有细粒度和内存密集型特征。随着对依赖这些截然不同用例的 AI 的强烈兴趣，再加上纳米尺度下摩尔定律的终结，需要在架构和底层执行模型方面采取重大替代方案。本文识别了一种创新的非冯·诺依曼架构——Continuum Computer Architecture（CCA），它重新定义了计算结构的本质，以在计算方法中产生强有力的创新，从而交付新一代高度并行的硬件架构。CCA 反映了一类高度并行架构，尽管在具体数量（例如内存块）上有所不同，但共享典型冯·诺依曼机器所不具备的多种属性。其中包括以内存为中心的组件、消息驱动的异步流控制，以及跨全局命名空间的轻量级乱序执行。在一种全新原创执行模型的指导下，这些创新的非冯·诺依曼架构属性共同提供了超越冯·诺依曼模型的新未来路径。本文记录了一系列相互关联的实验，这些实验共同确立了下一代非冯·诺依曼架构（尤其是图处理领域）的未来方向。
英文摘要：
Computer systems that have been successfully deployed for dense regular workloads fall short of achieving scalability and efficiency when applied to irregular and dynamic graph applications. Conventional computing systems rely heavily on static, regular, numeric intensive computations while High Performance Computing systems executing parallel graph applications exhibit little locality, spatial or temporal, and are fine-grained and memory intensive. With the strong interest in AI which depend on these very different use cases combined with the end of Moore's Law at nanoscale, dramatic alternatives in architecture and underlying execution models are required. This paper identifies an innovative non-von Neumann architecture, Continuum Computer Architecture (CCA), that redefines the nature of computing structures to yield powerful innovations in computational methods to deliver a new generation of highly parallel hardware architecture. CCA reflects a genus of highly parallel architectures that while varying in specific quantities (e.g., memory blocks), share a multiple of attributes not found in typical von Neumann machines. Among these are memory-centric components, message-driven asynchronous flow control, and lightweight out-of-order execution across a global name space. Together these innovative non-von Neumann architectural properties guided by a new original execution model will deliver the new future path for extending beyond the von Neumann model. This paper documents a series of interrelated experiments that together establish future directions for next generation non-von Neumann architectures, especially for graph processing.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
