Temporal motif mining is the task of finding the occurrences of subgraph patterns within a large input temporal graph that obey the specified structural and temporal constraints. Despite its utility in several critical application domains that demand high performance (e.g., detecting fraud in financial transaction graphs), the performance of existing software is limited on commercial hardware platforms, in that it runs for tens of hours. This paper presents Everest - a system that efficiently maps the workload of mining (supports both enumeration and counting) temporal motifs to the highly parallel GPU architecture. In particular, using an input temporal graph and a more expressive user-defined temporal motif query definition compared to prior works, Everest generates an execution plan and runtime primitives that optimize the workload execution by exploiting the high compute throughput of a GPU. Everest generates motif-specific mining code to reduce long-latency memory accesses and frequent thread divergence operations. Everest incorporates novel low-cost runtime mechanisms to enable load balancing to improve GPU hardware utilization. To support large graphs that do not fit on GPU memory, Everest also supports multi-GPU execution by intelligently partitioning the edge list that prevents inter-GPU communication. Everest hides the implementation complexity of presented optimizations away from the targeted system user for better usability. Our evaluation shows that, using proposed optimizations, Everest improves the performance of a baseline GPU implementation by 19x, on average.

翻译：时序模体挖掘是在大规模输入时序图中，寻找符合指定结构约束与时间约束的子图模式出现次数的任务。尽管该技术在多个对高性能有苛刻要求的关键应用领域（如金融交易图中的欺诈检测）具有实用价值，但现有软件在商用硬件平台上的性能受限，运行时长往往达数十小时。本文提出Everest——一种将时序模体挖掘（支持枚举与计数）工作负载高效映射至高度并行GPU架构的系统。具体而言，该系统以输入时序图及比先前工作更具表达力的用户定义时序模体查询定义为输入，通过利用GPU的高计算吞吐量生成执行计划与运行时原语以优化工作负载执行。Everest生成模体特定的挖掘代码以减少长延迟内存访问与频繁的线程分歧操作，并引入新型低开销运行时机制实现负载均衡以提升GPU硬件利用率。为支持无法完全载入GPU内存的大规模图，该系统还通过智能划分边列表实现多GPU执行，避免跨GPU通信。Everest将所提优化的实现复杂性对目标系统用户透明化，以提升易用性。实验表明，采用所提优化后，Everest可将基线GPU实现的性能平均提升19倍。