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This work will examine enhancements to the library for scalable, parallel pseudorandom number generation (SPRNG). SPRNG uses parameterization to produce many streams of random numbers with emphasis on parallel Monte Carlo methods. We extend the previous work to enable random access to these streams. This new method for generating streams improves both functionality and intuition of interface. Also considered are a few memory optimizations to the SPRNG library.
A Thesis Submitted to the Department of Computer Science in Partial Fulfillment of the Requirements for the Degree of Master of Science.
Includes bibliographical references.
Michael Mascagni, Professor Directing Thesis; Ashok Srinivasan, Committee Member; Alec Yasinsac, Committee Member; Robert van Engelen, Committee Member.
Florida State University
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