Abstract
One of the main challenges when accelerating financial applications using reconfigurable 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 of functional specialisations and the optimal data format for the Monte Carlo simulation, we allow different levels of programmability in our framework to retain good performance and support multiple applications. Designs targeting a Virtex-6 SX475T FPGA generated by our framework are about 40 times faster than single-core software implementations on an i7-870 quad-core CPU at 2.93 GHz; they are over 10 times faster and 20 times more energy efficient than 4-core implementations on the same i7-870 quad-core CPU, and are over three times more energy efficient and 36% faster than a highly optimised implementation on an NVIDIA Tesla C2070 GPU at 1.15 GHz. In addition, our framework is platform independent and can be extended to support CPU and GPU applications.
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References
ANTLR, http://www.antlr.org/
Boland, D., Constantinides, G.: Automated precision analysis: A polynomial algebraic approach. In: IEEE Int. Symp. on Field-Programmable Custom Computing Machines (FCCM) (2010)
de Dinechin, F., Pasca, B.: Floating-point exponential functions for DSP-enabled FPGAs. In: Proc. Int. Conf. on Field-Programmable Technology (2010)
Fang, C.F., Rutenbar, R.A., Chen, T.: Fast, accurate static analysis for fixed-point finite-precision effects in DSP designs. In: Proc. Int. Conf. on Computer-Aided Design (2003)
Fousse, L., Hanrot, G., Lefèvre, V., Pélissier, P., Zimmermann, P.: Mpfr: A multiple-precision binary floating-point library with correct rounding. ACM Trans. Math. Softw. 33 (2007)
Gaffar, A.A., Mencer, O., Luk, W., Cheung, P.Y.K.: Unifying bit-width optimisation for fixed-point and floating-point designs. In: IEEE Symp. on Field-Programmable Custom Computing Machines (2004)
Heath, D., Jarrow, R., Morton, A.: Bond pricing and the term structure of interest rates: A new methodology for contingent claims valuation. Econometrica 60(1), 77–105 (1992)
Ho, T.S.Y., Lee, S.B.: Term structure movements and pricing interest rate contingent claims. Journal of Finance 41(5), 1011–1029 (1986)
Jin, Q., Thomas, D.B., Luk, W., Cope, B.: Exploring reconfigurable architectures for tree-based option pricing models. ACM Trans. Reconfigurable Technol. Syst. 2, 21:1–21:17 (2009)
Kum, K.I., Sung, W.: Combined word-length optimization and high-level synthesis of digital signal processing systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 20, 921–930 (2001)
Larsen, R.J., Marx, M.L.: An Introduction to Mathematical Statistics and Its Applications. Pearson Education (2011)
Lee, D.U., Gaffar, A., Cheung, R., Mencer, O., Luk, W., Constantinides, G.: Accuracy-guaranteed bit-width optimization. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 25, 1990–2000 (2006)
Morris, G., Aubury, M.: Design space exploration of the European option benchmark using Hyperstreams. In: Proc. Int. Conf. on Field Programmable Logic and Applications, pp. 5–10 (2007)
Thomas, D.B., Luk, W.: High quality uniform random number generation using LUT optimised state-transition matrices. J. VLSI Signal Process. Syst. 47, 77–92 (2007)
Thomas, D., Bower, J., Luk, W.: Automatic generation and optimisation of reconfigurable financial Monte-Carlo simulations. In: Proc. Int. Conf. on Application-Specific Systems, Architectures and Processors, pp. 685–689 (2007)
Thomas, D., Luk, W.: Non-uniform random number generation through piecewise linear approximations. In: Proc. Int. Conf. on Field Programmable Logic and Applications (2006)
Tian, X., Benkrid, K.: American option pricing on reconfigurable hardware using least-squares monte carlo method. In: Proc. Int. Conf. on Field-Programmable Technology, pp. 263 –270 (2009)
Tse, A.H., Thomas, D.B., Tsoi, K., Luk, W.: Reconfigurable control variate Monte-Carlo designs for pricing exotic options. In: Proc. Int. Conf. on Field Programmable Logic and Applications, pp. 364–367 (2010)
Weston, S., Spooner, J., Racanière, S., Mencer, O.: Rapid computation of value and risk for derivatives portfolios. Concurrency and Computation: Practice and Experience (to appear)
Zhang, G., Leong, P., Ho, C., Tsoi, K., Cheung, C., Lee, D.U., Cheung, R., Luk, W.: Reconfigurable acceleration for Monte-Carlo based financial simulation. In: Proc. IEEE Int. Conf. on Field-Programmable Technology, pp. 215–224 (2005)
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Jin, Q. et al. (2012). Multi-level Customisation Framework for Curve Based Monte Carlo Financial Simulations. In: Choy, O.C.S., Cheung, R.C.C., Athanas, P., Sano, K. (eds) Reconfigurable Computing: Architectures, Tools and Applications. ARC 2012. Lecture Notes in Computer Science, vol 7199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28365-9_16
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DOI: https://doi.org/10.1007/978-3-642-28365-9_16
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