Advertisement

Self-aware Hardware Acceleration of Financial Applications on a Heterogeneous Cluster

  • Maciej KurekEmail author
  • Tobias Becker
  • Ce Guo
  • Stewart Denholm
  • Andreea-Ingrid Funie
  • Mark Salmon
  • Tim Todman
  • Wayne Luk
Chapter
Part of the Natural Computing Series book series (NCS)

Abstract

This chapter describes self-awareness in four financial applications. We apply some of the design patterns of Chapter 5 and techniques of Chapter 7. We describe three applications briefly, highlighting the links to self-awareness and self-expression. The applications are (i) a hybrid genetic programming and particle swarm optimisation approach for high-frequency trading, with fitness function evaluation accelerated by FPGA; (ii) an adaptive point process model for currency trading, accelerated by FPGA hardware; (iii) an adaptive line arbitrator synthesising high-reliability and low-latency feeds from redundant data feeds (A/B feeds) using FPGA hardware. Finally, we describe in more detail a generic optimisation approach for reconfigurable designs automating design optimisation, using reconfigurable hardware to speed up the optimisation process, applied to applications including a quadrature-based financial application. In each application, the hardware-accelerated self-aware approaches give significant benefits: up to 55× speedup for hardware-accelerated design optimisation compared to software hill climbing.

Keywords

Migration Cali Tocol Undersampling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Maciej Kurek
    • 1
    Email author
  • Tobias Becker
    • 1
  • Ce Guo
    • 1
  • Stewart Denholm
    • 1
  • Andreea-Ingrid Funie
    • 1
  • Mark Salmon
    • 2
  • Tim Todman
    • 1
  • Wayne Luk
    • 1
  1. 1.Imperial College LondonLondonUK
  2. 2.University of CambridgeLondonUK

Personalised recommendations