The increasing amount of trajectory data facilitates a wide spectrum of practical applications in which large numbers of trajectory range and similarity queries are issued continuously. This calls for high-throughput trajectory query processing. Traditional in-memory databases lack considerations of the unique features of trajectories, while specialized trajectory query processing systems are typically designed for only one type of trajectory queries. This paper introduces GAT, a unified GPU-accelerated framework to process batch trajectory queries with the objective of high throughput. GAT follows the filtering-and-verification paradigm where we develop a novel index GTIDX for effectively filtering invalid trajectories on the CPU, and exploit the massive parallelism of the GPU for verification. To optimize the performance of GAT, we first greedily partition batch queries to reduce the amortized query processing latency. We then apply the Morton-based encoding method to coalesce data access requests from the GPU cores, and maintain a hash table to avoid redundant data transfer between CPU and GPU. To achieve load balance, we group size-varying cells into balanced blocks with similar numbers of trajectory points. Extensive experiments have been conducted over real-life trajectory datasets. The results show that GAT is efficient, scalable, and achieves high throughput with acceptable indexing cost.

中文翻译：

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GAT：用于处理批处理轨迹查询的统一 GPU 加速框架

轨迹数据量的增加促进了广泛的实际应用，其中连续发出大量轨迹范围和相似性查询。这需要高吞吐量的轨迹查询处理。传统的内存数据库缺乏对轨迹独特特征的考虑，而专门的轨迹查询处理系统通常只针对一种类型的轨迹查询而设计。本文介绍了 GAT，这是一种统一的 GPU 加速框架，用于以高吞吐量为目标处理批量轨迹查询。GAT 遵循过滤和验证范式，我们开发了一种新颖的索引 GTIDX，用于有效过滤 CPU 上的无效轨迹，并利用 GPU 的大规模并行性进行验证。为了优化 GAT 的性能，我们首先对批量查询进行贪婪分区，以减少分摊的查询处理延迟。然后我们应用基于 Morton 的编码方法来合并来自 GPU 内核的数据访问请求，并维护一个哈希表以避免 CPU 和 GPU 之间的冗余数据传输。为了实现负载平衡，我们将大小不同的单元分组为具有相似轨迹点数量的平衡块。已经在现实生活轨迹数据集上进行了广泛的实验。结果表明，GAT 高效、可扩展，并以可接受的索引成本实现了高吞吐量。我们将大小不同的单元格分组为具有相似轨迹点数量的平衡块。已经在现实生活轨迹数据集上进行了广泛的实验。结果表明，GAT 高效、可扩展，并以可接受的索引成本实现了高吞吐量。我们将大小不同的单元格分组为具有相似轨迹点数量的平衡块。已经在现实生活轨迹数据集上进行了广泛的实验。结果表明，GAT 高效、可扩展，并以可接受的索引成本实现了高吞吐量。