Simulations on parallel computors require distinct streams of pseudo-random deviates for each processor. A combination generator is proposed which achieves distinct streams through a congruential component, and long period through a Fibonacci component. The algorithm has been coded in Fortran 77, and is suitable for fairly long simulations on machines of up to a thousand processors. © 1992, Taylor & Francis Group, LLC. All rights reserved
A reliable method of generating a high-volume of pseudo-random numbers is an essential requirement f...
Multiple independent streams of random numbers are often required in simulation studies, for instanc...
A pseudo-random number generator is presented which makes optimal use of the architecture of the i86...
We provide a review of the state of the art on the design and implementation of random number genera...
A significant problem faced by scientific investigation of complex modern systems is that credible s...
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Random number generators are used in many applications, from slot machines to simulations of nuclear...
We consider the requirements for uniform pseudo-random number generators on modern vector and parall...
An efficient and statistically reliable random number generator is one of the most important require...
To help promote more widespread adoption of hardware acceleration in parallel scientific computing, ...
Fast and reliable pseudo-random number generators are required for simulation and other applications...
In this article Re present background, rationale, and a description of the Scalable Parallel Random ...
We consider the requirements for uniform pseudo-random number generators on modern vector and parall...
A Fortran implementation f a random number generator is described whmh produces a sequence of random...
We will look at random number generation from the point-of-view of Monte Carlo computations. Thus...
A reliable method of generating a high-volume of pseudo-random numbers is an essential requirement f...
Multiple independent streams of random numbers are often required in simulation studies, for instanc...
A pseudo-random number generator is presented which makes optimal use of the architecture of the i86...
We provide a review of the state of the art on the design and implementation of random number genera...
A significant problem faced by scientific investigation of complex modern systems is that credible s...
International audienceWe provide a review of the state of the art on the design and implementation o...
Random number generators are used in many applications, from slot machines to simulations of nuclear...
We consider the requirements for uniform pseudo-random number generators on modern vector and parall...
An efficient and statistically reliable random number generator is one of the most important require...
To help promote more widespread adoption of hardware acceleration in parallel scientific computing, ...
Fast and reliable pseudo-random number generators are required for simulation and other applications...
In this article Re present background, rationale, and a description of the Scalable Parallel Random ...
We consider the requirements for uniform pseudo-random number generators on modern vector and parall...
A Fortran implementation f a random number generator is described whmh produces a sequence of random...
We will look at random number generation from the point-of-view of Monte Carlo computations. Thus...
A reliable method of generating a high-volume of pseudo-random numbers is an essential requirement f...
Multiple independent streams of random numbers are often required in simulation studies, for instanc...
A pseudo-random number generator is presented which makes optimal use of the architecture of the i86...
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