Generating massive high-quality random numbers using GPU

— Pseudo-random number generators (PRNG) have been intensively used in many stochastic algorithms in artificial intelligence, computer graphics and other scientific computing. However, the current commodity GPU design does not facilitate the efficient implementation of high-quality PRNGs that require high-precision integer arithmetics and bitwise operations. In this paper, we propose a framework to generate a high-quality PRNG shader for all kinds of GPUs. We adopt the cellular automata (CA) PRNG to facilitate high speed and parallel random number generation. The configuration of the CA PRNG is completed automatically by optimizing an objective function that accounts for quality of generated random sequences. To visually evaluate the result, we apply the best PRNG shader to photon mapping. Timing statistics show that our GPU parallelized PRNG is much faster than a pure CPU implementation.

• Type: Conference
• Year: 2008
• Where: CEC
• Authors: Wai-Man Pang, Tien-Tsin Wong, Pheng-Ann Heng
• Keywords: Artificial Intelligence, CEC 2008, Current Commodity Gpu, PRNG Shader, Pseudo-random Number Generators