RAM-Based Random Sequence Generator for Gene Simulations
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Solution Overview
Problem
Current random number generators, such as linear-feedback shift registers, fail to provide unique values efficiently for synchronous Boolean network simulations, leading to slow simulation times due to the need for ranked update orders and the risk of repeated index generation in gene regulatory network models.
Innovation Solution
A method and hardware-based random sequence generator that pre-loads a RAM block with defined values and uses a counter and random offset to shuffle the sequence, ensuring unique index generation and fast random number generation, optimized for gene regulatory network simulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If linear-feedback shift register is used for generating random numbers, then the generation process is simple, but it cannot guarantee unique values and slows down simulation
Solution Approach 1:
The patent pre-generates and stores a complete sequence of unique random values in a lookup table before simulation begins. During simulation, pre-stored unique random values are simply retrieved rather than generated on-the-fly, eliminating the conflict between generation simplicity and value uniqueness.
Solution Approach 2:
Instead of using a complex random number generator that guarantees uniqueness, the patent creates a pre-computed copy of all possible unique random values in a lookup table. This copy allows fast retrieval without regenerating values, resolving the contradiction between simple generation and unique value guarantee.
2Adaptability or versatility
If asynchronous update schemes are used to handle diversity in Boolean models, then model flexibility is improved, but computational cost increases
Solution Approach 1:
The system uses pre-computed random update sequences that automatically adapt to different model configurations without requiring complex runtime decisions. The lookup table self-services by providing ready-made update orders, reducing computational overhead while maintaining flexibility.
3Measurement precision
If ranked update orders are implemented to update nodes in specific sequence, then simulation accuracy is improved, but multiple random ranges are required increasing complexity
Solution Approach 1:
A single lookup table serves multiple purposes: it provides both the random update sequencing and the ranked update orders needed for different simulation requirements. This universal structure eliminates the need for multiple separate random number generators and reduces system complexity while maintaining simulation accuracy.
Data Source
AI summary
A random sequence generation of defined values may be provided. A method comprises pre-loading a RAM block with an initial list comprising the defined values of a sequence of values to be updated, and shuffling the defined values of the sequence using a counter and a random offset for indices in the list.