Quasirandom Number Generators for Parallel Monte Carlo Algorithms
نویسنده
چکیده
A method for generating sequences of quasirandom numbers allows conventional serial Monte Carlo algorithms to be parallelized with no loss of computation eeciency. Speciically, a Sobol' sequence can be broken up into interleaved subsets; with each processing node calculating a unique subset of the full sequence, all of the computational advantages of quasirandom Monte Carlo methods over pure-random algorithms or grid-based techniques are retained. Tests with several parallel supercomputers demonstrate that greater than 10 5 integration points (1D{6D regions) can be generated per second per node, independent of the number of nodes.
منابع مشابه
Efficient Generation of Parallel Quasirandom Faure Sequences Via Scrambling
Much of the recent work on parallelizing quasi-Monte Carlo methods has been aimed at splitting a quasirandom sequence into many subsequences which are then used independently on the various parallel processes. This method works well for the parallelization of pseudorandom numbers, but due to the nature of quality in quasirandom numbers, this technique has many drawbacks. In contrast, this paper...
متن کاملSccs-746 Tests of Random Number Generators Using Ising Model Simulations
Large-scale Monte Carlo simulations require high-quality random number generators to ensure correct results. The contrapositive of this statement is also true – the quality of random number generators can be tested by using them in large-scale Monte Carlo simulations. We have tested many commonly-used random number generators with high precision Monte Carlo simulations of the 2-d Ising model us...
متن کاملTests of random number generators using Ising model simulations
Large-scale Monte Carlo simulations require high-quality random number generators to ensure correct results. The contrapositive of this statement is also true – the quality of random number generators can be tested by using them in large-scale Monte Carlo simulations. We have tested many commonly-used random number generators with high precision Monte Carlo simulations of the 2-d Ising model us...
متن کاملThe Florida State University College of Arts and Science Scrambled Quasirandom Sequences and Their Applications
Quasi-Monte Carlo methods are a variant of ordinary Monte Carlo methods that employ highly uniform quasirandom numbers in place of Monte Carlo’s pseudorandom numbers. Monte Carlo methods offer statistical error estimates; however, while quasi-Monte Carlo has a faster convergence rate than normal Monte Carlo, one cannot obtain error estimates from quasi-Monte Carlo sample values by any practical...
متن کاملA Parallel Quasi-Monte Carlo Method for Solving Systems of Linear Equations
This paper presents a parallel quasi-Monte Carlo method for solving general sparse systems of linear algebraic equations. In our parallel implementation we use disjoint contiguous blocks of quasirandom numbers extracted from a given quasirandom sequence for each processor. In this case, the increased speed does not come at the cost of less thrust-worthy answers. Similar results have been report...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- J. Parallel Distrib. Comput.
دوره 38 شماره
صفحات -
تاریخ انتشار 1996