Time-SWAD: A dataflow engine for time-based single window stream aggregation
Paper in proceedings, 2019

High throughput and low latency streaming aggregation is essential for many applications that analyze massive volumes of data in real-time. Incoming data need to be stored in a single sliding window before processing, in cases where incremental aggregations are wasteful or not possible at all; this puts tremendous pressure to the memory bandwidth. In addition, particular problems call for time-based windows, defined by a time-interval, where the amount of data per window may vary and as a consequence are more challenging to handle. This paper describes Time-SWAD, the first accelerator for time-based single-window stream aggregation. Time-SWAD is a dataflow engine (DFE), implemented on a Maxeler machine, offering high processing throughput, up to 150 Mtuples/sec, similar to related GPU systems, which however do not support both time-based and single windows. It uses a direct feed of incoming data from the network and has direct access to off-chip DRAM, enabling ultra-low processing latency of 1-10 μsec, at least 4 orders of magnitude lower than software-based solutions.

Stream

Time based

Dataflow

FPGA

Aggregation

Author

Prajith Ramakrishnan Geethakumari

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers), Computer Systems

Vincenzo Massimiliano Gulisano

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Pedro Petersen Moura Trancoso

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

Ioannis Sourdis

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers), Computer Systems

Proceedings - 2019 International Conference on Field-Programmable Technology, ICFPT 2019

Vol. 2019-December 72-80 8977927

18th International Conference on Field-Programmable Technology, ICFPT 2019
Tianjin, China,

Subject Categories

Computer Engineering

Computer Science

Computer Systems

DOI

10.1109/ICFPT47387.2019.00017

More information

Latest update

6/25/2020