Random Number Generation Circuit Scaling via Logical Operations
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Solution Overview
Problem
The increasing demand for normal random numbers in simulations and numerical analyses leads to a rise in the hardware scale and cost of random number generation devices, necessitating a method to generate a larger number of normal random numbers while minimizing the circuit scale.
Innovation Solution
The proposed solution involves a random number generation device with multiple uniform random number generators and normal random number generators that perform logical operations on bit values to generate a larger number of normal random numbers, utilizing the central limit theorem to achieve this while reducing the circuit scale by configuring uniform random number generators as simple circuits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple uniform random number generators are used to generate more normal random numbers, then the number of generated normal random numbers increases, but the hardware scale and cost increase
Solution Approach 1:
The device is divided into multiple functional units: multiple uniform random number generators (first and second types) and multiple normal random number generators. Each unit has a specific function, and they work in parallel to generate multiple normal random numbers simultaneously, improving productivity while keeping each individual unit relatively simple
Solution Approach 2:
Multiple uniform random number generators and normal random number generators are combined into a single integrated device. The uniform random number generators share common resources and the normal random number generators process outputs from multiple uniform generators together, achieving economies of scale and reducing overall hardware complexity
2Device complexity
If the circuit scale is reduced to minimize cost, then the hardware cost decreases, but the ability to generate sufficient normal random numbers for simulations is compromised
Solution Approach 1:
The device uses different types of uniform random number generators (first type and second type) with different parameters and characteristics. By varying the parameters of the generators and using logical operations on their outputs, the system maintains high-quality normal distribution while using simpler, smaller-scale circuits
Solution Approach 2:
Uniform random numbers serve as an intermediary between the simple uniform random number generators and the more complex normal random number generation process. The uniform random numbers are generated by simple circuits, then transformed into normal random numbers through established mathematical methods, allowing circuit scale reduction while maintaining generation capability
Data Source
AI summary
A random number generation device includes: a plurality of first uniform random number generators configured to respectively generate a plurality of first uniform random numbers; a plurality of first normal random number generators configured to respectively generate a plurality of first normal random numbers based on the plurality of first uniform random numbers; a plurality of second uniform random number generators configured to perform a logical operation on bit values of two or more of the first uniform random numbers to respectively generate a plurality of second uniform random numbers; and at least one second normal random number generator configured to generate at least one second normal random number based on the plurality of second uniform random numbers.