论文标题
平行图分析的要素
Essentials of Parallel Graph Analytics
论文作者
论文摘要
我们将图形数据结构，前沿，操作员，迭代环结构和收敛条件确定为基于天然图形方法的图分析系统的重要组成部分。使用这些基本组件，我们提出了一个抽象，该抽象捕获图形分析中的所有重要编程模型，例如散装同步，异步，共享 - 内存，消息 - 录音和推动与拉动遍历。最后，我们通过单源最短路径及其所需组件的优雅现代C ++实现来证明抽象的力量。
We identify the graph data structure, frontiers, operators, an iterative loop structure, and convergence conditions as essential components of graph analytics systems based on the native-graph approach. Using these essential components, we propose an abstraction that captures all the significant programming models within graph analytics, such as bulk-synchronous, asynchronous, shared-memory, message-passing, and push vs. pull traversals. Finally, we demonstrate the power of our abstraction with an elegant modern C++ implementation of single-source shortest path and its required components.
