Why The Results of Parallel and Serial Monte Carlo Simulations May Differ
Boris D. Lubachevsky
TL;DR
This paper investigates why parallel and serial Monte Carlo simulations sometimes produce different results, highlighting issues related to random number generators and their impact on simulation accuracy.
Contribution
It identifies the causes of discrepancies between parallel and serial Monte Carlo results, emphasizing the role of random number generator faults.
Findings
Parallel simulations can reveal faults in random number generators.
Differences in results are often due to generator faults or correlations.
The study provides guidelines for diagnosing and mitigating these issues.
Abstract
Parallel Monte Carlo simulations often expose faults in random number generators
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Taxonomy
TopicsTheoretical and Computational Physics · Benford’s Law and Fraud Detection · Algorithms and Data Compression