Graph is a significant data structure that describes the relationship between entries. Many application domains in the real world are heavily dependent on graph data. However, graph applications are vastly different from traditional applications. It is inefficient to use general-purpose platforms for graph applications, thus contributing to the research of specific graph processing platforms. In this survey, we systematically categorize the graph workloads and applications, and provide a detailed review of existing graph processing platforms by dividing them into general-purpose and specialized systems. We thoroughly analyze the implementation technologies including programming models, partitioning strategies, communication models, execution models, and fault tolerance strategies. Finally, we analyze recent advances and present four open problems for future research.

图形是描述条目之间关系的重要数据结构。现实世界中的许多应用程序域都严重依赖于图形数据。但是，图形应用程序与传统应用程序有很大不同。将通用平台用于图形应用程序效率低下，从而为特定图形处理平台的研究做出了贡献。在本次调查中，我们对图形工作负载和应用程序进行了系统分类，并通过将它们分为通用系统和专用系统对现有图形处理平台进行了详细介绍。我们彻底分析了实现技术，包括编程模型，分区策略，通信模型，执行模型和容错策略。最后，