The use of High Performance Computing (HPC) in capital markets has witnessed considerable growth in the past decade. In particular, electronic trading in globalized markets and exchanges requires sophisticated communication and data management to support the massive amount of incoming streaming data where the main problem is in latency management. In addition, novel algorithms for trading may incorporate computational intelligence techniques in order to implement and improve the current decision making process. Multi-Agent Systems (MAS) have been recognized as a feasible solution to address complex problems in many areas and appear an innovative, powerful and flexible solution for implementing trading engines. On other hand, reconfigurable hardware and in particular Field Programmable Gate Arrays (FPGA) offers performance benefits over conventional software implementations, and seems to be the next logical step in the development of multi-agent technology. However, only a very limited number of projects have reported multi-agent implementations in reconfigurable hardware. Current agent oriented programming (AOP) methodologies are not entirely appropriate for the design and deployment of MAS at microchip level, making agents in hardware difficult to engineer. This arises because there is no clear methodology for their design that incorporates a similar level of conceptualization to software implementations, while at the same time takes into account the specific requirements for FPGAs. This thesis presents as its main contributions a novel methodology to implement MAS in FPGA using the Event-Driven Reactive Architecture (EDRA) at agent level and a hierarchical Network-on- Chip (NoC) approach at societal level, presenting an agent-based trading engine as a validation scenario. EDRA is proposed to design and implement the internal architecture of hardware-based scenario. EDRA is proposed to design and implement the internal architecture of hardware-based agents allowing one to overcome the absence of a well-defined procedure to model and deploy a MAS in reconfigurable hardware. It uses a fine-grained task decomposition inside agents to generate reactive behaviours and link them with consistent hardware interfaces to enable internal flow of information, favouring modular constructions, flexibility and re-use of structures. The communication model at societal level consists of a combination of a Star-NoC topology, scaling in a hierarchical fashion by means of the integration of lower level clusters of agents and routers, in conjunction with a message broadcast mechanism through standardized interfaces using the Open Core Protocol (OCP). A router microarchitecture and network adapters are designed to interface EDRA agents into the NoC. In conjunction, EDRA and the Star-NoC allow for the design of Multi- Agent System-on-Chip (MASoC), extending an agent oriented design model to the realm of hardware design. Furthermore, this thesis demonstrates how to use the proposed model to design and deploy an agent-based trading engine, implemented in an Altera Stratix IV FPGA. With this application an agent-based High Performance Computing platform for financial applications is created, but a Machine Learning (ML) technique as a mean to increment the agent’s cognitive capabilities is also included, achieving a performance adequate for practical High Frequency Trading (HFT) applications.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:680141 |
| Date | January 2015 |
| Creators | Gerlein, Eduardo |
| Publisher | Ulster University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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