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Enabling Stateful Functions for Stream Processing in the Programmable Data Plane

Published: 27 June 2022 Publication History

Abstract

Sensor-rich environments are crucial components of the Internet of Things ecosystem and benefit from real-time applications. Many applications perform real-time analytics on these IoT workloads by performing continuous stream processing for a window of sequence data elements. However, executing light-weight stateful functions on server CPUs adds to the communication latency of each small message in a high data rate environment, primarily due to messages traveling through a complex network stack to reach the CPU. Thus, we present an in-network function deployment architecture with low latency and low resource footprint by introducing a new compute layer. We propose an FPGA-based Switch/NIC prototype with a compute layer utilizing RISC-V soft cores and High-Level Synthesis modules. We evaluate the design for two microbenchmarks on a Zynq 7000 FPGA each, achieving less than 10 μs in latency and consuming less than 6 % of resources.

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Cited By

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  • (2023)INDIANA—In-Network Distributed Infrastructure for Advanced Network ApplicationsThe International Journal of High Performance Computing Applications10.1177/1094342023117966237:3-4(442-461)Online publication date: 26-Jun-2023

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Published In

cover image ACM Conferences
HiPS '22: Proceedings of the 2nd Workshop on High Performance Serverless Computing
June 2022
36 pages
ISBN:9781450393119
DOI:10.1145/3526060
  • General Chairs:
  • Yadu Babuji,
  • Kyle Chard,
  • Ian Foster,
  • Zhuozhao Li
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Publication History

Published: 27 June 2022

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Author Tags

  1. fpga
  2. in-network computing
  3. programmable networks
  4. risc-v soft core
  5. stateful faas
  6. stream processing

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  • (2023)INDIANA—In-Network Distributed Infrastructure for Advanced Network ApplicationsThe International Journal of High Performance Computing Applications10.1177/1094342023117966237:3-4(442-461)Online publication date: 26-Jun-2023

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