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Several software efforts have been produced over the past few years in various programming languages to help developers handle pseudorandom streams partitioning. Parallel and distributed stochastic simulations can obviously benefit from this kind of high‒level tools. The latest release of the Java Development Kit (JDK 7) tries to tackle this problem by providing facilities to partition a pseudorandom...
At the manycore era, every simulation practitioner can take advantage of the computing horsepower delivered by the available high performance computing devices. From multicore CPUs (Central Processing Unit) to thousand-thread GPUs (Graphics Processing Unit), several architectures are now able to offer great speed-ups to simulations. However, it is often tricky to harness them properly, and even more...
Parallel And Distributed Simulations (PADS) become more and more spread since scientists always want more accurate results in the shortest time. PADS are often sensitive to several parameters, and when they own a stochastic component, one has to ensure he knows how to correctly deal with randomness in a parallel application. This point can appear to be very tricky for non-experts, who might be tempted...
Stochastic simulations are often sensitive to the randomness source that characterizes the statistical quality of their results. Consequently, we need highly reliable Random Number Generators (RNGs) to feed such applications. Recent developments try to shrink the computation time by using more and more General Purpose Graphics Processing Units (GP-GPUs) to speed-up stochastic simulations. Such devices...
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