clQMC
An OpenCL library for quasi-Monte Carlo methods
Bibliography
[1]

J. Dick and F. Pillichshammer. Digital Nets and Sequences: Discrepancy Theory and Quasi-Monte Carlo Integration. Cambridge University Press, Cambridge, U.K., 2010.

[2]

P. L'Ecuyer and C. Lemieux. Variance reduction via lattice rules. Management Science, 46(9):1214–1235, 2000.

[3]

P. L'Ecuyer and D. Munger. On figures of merit for randomly-shifted lattice rules. In H. Wozniakowski and L. Plaskota, editors, Monte Carlo and Quasi-Monte Carlo Methods 2010, pages 133–159, Berlin, 2012. Springer-Verlag.

[4]

P. L'Ecuyer and D. Munger. Lattice builder: A general software tool for constructing rank-1 lattice rules. ACM Transactions on Mathematical Software, 2015. to appear, see http://www.iro.umontreal.ca/ lecuyer/papers.html.

[5]

P. L'Ecuyer. SSJ: A Java Library for Stochastic Simulation, 2008. Software user's guide, available at http://www.iro.umontreal.ca/ lecuyer.

[6]

P. L'Ecuyer. Quasi-Monte Carlo methods with applications in finance. Finance and Stochastics, 13(3):307–349, 2009.

[7]

C. Lemieux. Monte Carlo and Quasi-Monte Carlo Sampling. Springer-Verlag, New York, NY, 2009.

[8]

H. Niederreiter. New methods for pseudorandom number and pseudorandom vector generation. In Proceedings of the 1992 Winter Simulation Conference, pages 264–269. IEEE Press, 1992.

[9]

Dirk Nuyens. The construction of good lattice rules and polynomial lattice rules. In Peter Kritzer, Harald Niederreiter, Friedrich Pillichshammer, and Arne Winterhof, editors, Radon Series on Computational and Applied Mathematics. De Gruyter, 2014. to appear.

[10]

I. H. Sloan and S. Joe. Lattice Methods for Multiple Integration. Clarendon Press, Oxford, 1994.