Anson H. T. Tse

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—Monte-Carlo (MC) simulation is an effective tool for solving complex problems such as many-body simulation, exotic option pricing and partial differential equation solving. The huge amount of computation in MC makes it a good candidate for acceleration using hardware and distributed computing platforms. In this work, we propose a novel MC simulation(More)
This paper presents an architecture for FPGA acceleration of quadrature methods used for pricing complex options, such as discrete barrier, Bermudan, and Ameri-can options. The architecture can be optimized for speed and power consumption by exploiting pipelining and par-allelism to produce efficient implementations in reconfig-urable logic. An optimised(More)
This paper presents a generic precision optimisation methodology for quadrature computation targeting reconfigurable hardware to maximise performance at a given error tolerance level. The proposed methodology optimises performance by considering integration grid density versus mantissa size of floating-point operators. The optimisation provides the number(More)
Arithmetic Asian options are financial derivatives which have the feature of path-dependency: they depend on the entire price path of the underlying asset, rather than just the instantaneous price. This path-dependency makes them difficult to price, as only computationally intensive Monte-Carlo methods can provide accurate prices. This paper proposes an(More)
This paper introduces a novel mixed precision methodology applicable to any Monte Carlo (MC) simulation. It involves the use of data-paths with reduced precision, and the resulting errors are corrected by auxiliary sampling. An analytical model is developed for a reconfigurable accelerator system with a field-programmable gate array (FPGA) and a general(More)
—Exotic options are financial derivatives which have complex features including path-dependency. These complex features make them difficult to price, as only computationally intensive Monte-Carlo methods can provide accurate prices. This paper proposes an FPGA-accelerated control variate Monte-Carlo (CVMC) framework for pricing exotic options. An opti-mised(More)
—This paper presents a novel parallel architecture for accelerating quadrature methods used for pricing complex multi-dimensional options, such as discrete barrier, Bermudan and American options. We explore different designs of the quadrature evaluation core including optimized pipelined hardware designs in reconfigurable logic and a compute unified device(More)
We describe a programming framework for high performance clusters with various hardware accelerators. In this framework, users can utilize the available heterogeneous resources productively and efficiently. The distributed application is highly modularized to support dynamic system configuration with changing types and number of the accelerators. Multiple(More)
One of the main challenges when accelerating financial applications using recon-figurable hardware is the management of design complexity. This paper proposes a multi-level customisation framework for automatic generation of complex yet highly efficient curve based financial Monte Carlo simulators on reconfigurable hardware. By identifying multiple levels(More)
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