An efficient and scalable implementation of sliding-window aggregate operator on FPGA

This paper presents an efficient and scalable implementation of an FPGA-based accelerator for sliding-window aggregates over disordered data streams. With an increasing number of overlapping sliding-windows, the window aggregates have a serious scalability issue, especially when it comes to implementing them in parallel processing hardware (e.g., FPGAs). To address the issue, we propose a resource-efficient, scalable, and order-agnostic hardware design and its implementation by examining and integrating two key concepts, called Window-ID and Pane, which are originally proposed for software implementation, respectively. Evaluation results show that the proposed implementation scales well compared to the previous FPGA implementation in terms of both resource consumption and performance. The proposed design is fully pipelined and our implementation can process out-of-order data items, or tuples, at wire speed up to 200 million tuples per second.