DocumentCode :
2251828
Title :
Parallel GPU-accelerated recursion-based generators of pseudorandom numbers
Author :
Stpiczynski, Przemyslaw ; Szalkowski, Dominik ; Potiopa, Joanna
Author_Institution :
Maria Curie-Sklodowska Univ., Lublin, Poland
fYear :
2012
fDate :
9-12 Sept. 2012
Firstpage :
571
Lastpage :
578
Abstract :
The aim of the paper is to show how to design fast parallel algorithms for linear congruential and lagged Fibonacci pseudorandom numbers generators. The new algorithms employ the divide-and-conquer approach for solving linear recurrence systems and can be easily implemented on GPU-accelerated hybrid systems using CUDA or OpenCL. Numerical experiments performed on a computer system with modern Fermi GPU show that they achieve good speedup in comparison to the standard CPU-based sequential algorithms.
Keywords :
divide and conquer methods; graphics processing units; mathematics computing; numerical analysis; parallel algorithms; parallel architectures; random number generation; CUDA; GPU-accelerated hybrid systems; OpenCL; computer system; divide-and-conquer approach; fast parallel algorithm design; lagged Fibonacci pseudorandom numbers generators; linear congruential Fibonacci pseudorandom numbers generators; linear recurrence systems; parallel GPU-accelerated recursion-based generators; Computer architecture; Generators; Graphics processing units; Instruction sets; Libraries; Parallel processing; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Systems (FedCSIS), 2012 Federated Conference on
Conference_Location :
Wroclaw
Print_ISBN :
978-1-4673-0708-6
Electronic_ISBN :
978-83-60810-51-4
Type :
conf
Filename :
6354460
Link To Document :
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