Inhaltsangabe
A practical overview of generating random numbers for large-scale parallel computing. It explains how to keep Monte Carlo simulations reproducible and efficient when using many processors.
The material surveys different parallel architectures and the challenges these machines pose, such as load balancing, asynchronous execution, and migrating tasks. It then focuses on pseudorandom streams used by simulation processes, not just hardware generators. You’ll see approaches for creating independent sequences, including the idea of a pseudorandom tree where new streams are launched as simulations branch. The text compares classic generator families and offers pragmatic options for long, nonoverlapping sequences that help reduce variance across replicas. It also introduces the spectral test as a way to measure uniformity and independence across multiple dimensions, and it discusses how to arrange constants to improve independence and reproducibility without sacrificing performance.
- How to map random number streams to simulation processes or threads.
- Different strategies for branching and migrating random streams across processors.
- What the spectral test measures and how it guides generator selection.
- Practical guidance on choosing additive constants to create independent, long sequences.
Ideal for readers of parallel computing and Monte Carlo methods who want a grounded, implementable approach to random number generation on large, evolving systems.
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Random Number Generators for Ultracomputers (Classic Reprint)
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Paperback. Zustand: New. Print on Demand. This book delves into the intricacies of designing pseudorandom number generators specifically tailored for the unique challenges posed by parallel computing architectures. It addresses the need for reproducibility in Monte Carlo simulations, where the ability to retrace computational steps is crucial for debugging complex programs and ensuring the validity of ported code. The author explores the concept of pseudorandom trees, where multiple independent sequences are generated to support branching processes and load balancing in parallel computations. This approach ensures that simulations remain consistent and efficient, even when processes migrate across processors or the number of available processors fluctuates. Delving into the mathematical foundations of random number generation, the book examines linear congruential generators and their correlation properties. The author introduces a spectral test to assess the uniformity and independence of parallel streams, providing insights into selecting appropriate parameters for these generators. By addressing the challenges of reproducibility, long sequences, and independence in parallel computing environments, this book offers valuable guidance for researchers and practitioners working with Monte Carlo simulations. Its insights contribute to the advancement of reliable and efficient computational methods in various scientific and engineering domains. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Bestandsnummer des Verkäufers 9781334538582_0
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Random Number Generators for Ultracomputers Classic Reprint
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Random Number Generators for Ultracomputers Classic Reprint
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