Speaker
Description
Sequences of pseudorandom numbers of high statistical quality and their
efficient generation are critical for the use of Monte Carlo simulation
in many areas of computational science. As high performance parallel
computing systems equipped with wider vector pipelines or many-cores
technologies become widely available, a variety of parallel pseudo-random
number generators (PRNGs) are being developed for specific hardware
architectures such as SIMD or GPU. However, portable libraries of
random number services which can be used across different architectures
and in hybrid computing models are not commonly available. We report on
an initial implementation of library portable across serial CPUs, vector
CPUs, accelerators and GPUs which rely on a common source code implementation
for robustness and which use efficient implementations for most operations on
each category of hardware. Results of preliminary performance evaluation and
statistical tests are presented as well.
