Mathematics

    Parallel Algorithms for Generating Large Tables of Primes

    Kathy Liszka
    Associate Professor of Mathematical Sciences
     

                                                               Funding Sources
                                                              
    Description of the Project
                                                              
    High Performance Computing Sources
                                                              
    Projected Benefits of the Project
                                                              
    Collaborations
     

    Funding Sources

NSF Grant CCR-9634559

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    Description of the Project

The search for efficient algorithms to produce large primes is motivated largely by the needs of cryptologists and number theorists.41-43 The focus of the project is to investigate variations on sieving algorithms to generate very large tables of primes efficiently using parallel architectures.  Testing and implementation of the algorithms are based on selected mapping and communication structures that are determined to be optimal.  Of special interest is insight into the scope of memory limitations that must be addressed in order to generate primes to 10 18.  Break even points between various algorithms are being identified to determine how feasible it is to reach a certain point given a particular algorithm.

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    High Performance Computing Sources

This project requires high-speed network access for moving large file of primes, both for initial setups in some algorithms, and for the final results on remote computers.  The connections are to the Ohio Super Computer Center and Purdue University.

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    Projected Benefits of the Project

Currently it is not feasible to store data files of the size needed for primes up to 1013 or larger, at the remote sites. It is necessary to transport the data back to the local site so that testing may be done on the data to verify correctness. This application requires visualization of 10-40 Mbyte files within 10 seconds.

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    Collaborations

    John K. Antonio, Texas Tech University, H.J. Siegel, Purdue University, Samuel S Wagstaff, Purdue University

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