Streaming processing is an important and growing class of applications for analyzing continuous streams in real time. In such applications, sliding-window aggregation (SWAG) is a widely used approach, and general-purpose processors cannot efficiently handle SWAG because of the specific computation patterns. This article proposes an efficient dataflow accelerator architecture for ubiquitous SWAGs, called ShuntFlowPlus. ShuntFlowPlus supports two main categories of SWAGs that are widely used in streaming processing. Meanwhile, we propose a shunt rule to enable ShuntFlowPlus to efficiently handle SWAGs with arbitrary parameters. Furthermore, we propose a novel realization scheme of SWAG kernels based on buffer sharing to maximize buffer utilization. As a case study, we implemented ShuntFlowPlus on an Altera Arria 10 AX115N FPGA board at 150 MHz and compared it to previous approaches. The experimental results show that ShuntFlowPlus provides a tremendous throughput and latency advantage over CPU and GPU implementations on both reduce-like and index-like SWAGs. Compare to ShuntFlow, 41% of buffer resources are saved.

流处理是用于实时分析连续流的一类重要且不断增长的应用程序。在此类应用中，滑动窗口聚合 (SWAG) 是一种广泛使用的方法，由于特定的计算模式，通用处理器无法有效处理 SWAG。本文为无处不在的 SWAG 提出了一种高效的数据流加速器架构，称为 ShuntFlowPlus。ShuntFlowPlus 支持在流处理中广泛使用的两大类 SWAG。同时，我们提出了一个分流规则，使 ShuntFlowPlus 能够有效地处理具有任意参数的 SWAG。此外，我们提出了一种基于缓冲区共享的 SWAG 内核的新实现方案，以最大限度地提高缓冲区利用率。作为案例研究，我们在 150 MHz 的 Altera Arria 10 AX115N FPGA 板上实现了 ShuntFlowPlus，并将其与之前的方法进行了比较。实验结果表明，在类缩减和类索引 SWAG 上，ShuntFlowPlus 比 CPU 和 GPU 实现提供了巨大的吞吐量和延迟优势。与 ShuntFlow 相比，节省了 41% 的缓冲区资源。