Hieroglyph: Locally-Sufficient Graph Processing via Compute-Sync-Merge

Xiaoen Ju, H. Jamjoom, K. Shin
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引用次数: 2

Abstract

Mainstream graph processing systems (such as Pregel [3] and PowerGraph [1]) follow the bulk synchronous parallel model. This design leads to the tight coupling of computation and communication, where no vertex can proceed to the next iteration of computation until all vertices have been processed in the current iteration and graph states have been synchronized across all hosts. This coupling of computation and communication incurs significant performance penalty. Fully decoupling computation from communication requires (i) restricted access to only local state during computation and (ii) independence of inter-host communication from computation. We call the combination of both conditions local sufficiency. Local sufficiency is not efficiently supported by state of the art. Synchronous systems, by design, do not support local sufficiency due to their intrinsic computation-communication coupling. Even systems that implement asynchronous execution only partially achieve local sufficiency. For example, PowerGraph's asynchronous mode satisfies local sufficiency by distributed scheduling.
象形文字:通过计算同步合并的局部充分图形处理
主流的图形处理系统(如Pregel[3]和PowerGraph[1])采用的是批量同步并行模型。这种设计导致了计算和通信的紧密耦合,在当前迭代中处理所有顶点并且在所有主机上同步图形状态之前,任何顶点都不能进行下一次计算迭代。这种计算和通信的耦合导致了显著的性能损失。将计算与通信完全解耦需要(i)在计算期间限制仅访问本地状态和(ii)主机间通信与计算的独立性。我们把这两种条件的结合称为局部充分性。当地的自给自足并没有得到最先进技术的有效支持。根据设计,同步系统由于其固有的计算-通信耦合而不支持局部充分性。即使是实现异步执行的系统也只能部分地实现本地充分性。例如,PowerGraph的异步模式通过分布式调度来满足本地充分性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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