Reduced Local Models for Physics Simulation Instancing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for instancing large-scale physics simulations are inefficient due to the need to re-run the entire simulation for each small modification, especially in scenarios with frequent changes to the simulation environment, leading to high computational costs and resource usage.
Innovation Solution
A computer-implemented method that involves providing a set of local simulations, computing reduced models for each, and reusing these models to instantiate global simulations, thereby reducing the need for recalculation and optimizing resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire simulation is re-run for each scene modification, then the simulation accuracy is maintained, but the computational cost and time consumption increase exponentially
Solution Approach 1:
The patent divides the global simulation into multiple independent local simulations that can be computed separately. Each local simulation corresponds to a specific zone of interest and can be pre-computed and stored. When instancing is needed, only the relevant local simulations are retrieved and combined, avoiding the need to re-run the entire global simulation. This segmentation resolves the contradiction by maintaining accuracy through localized computations while dramatically reducing computational time.
Solution Approach 2:
The patent pre-computes and stores local simulations before they are needed for instancing. By performing the computationally intensive work in advance and caching the results, the system avoids repeating the same calculations when scene modifications occur. This preliminary action maintains simulation accuracy while reducing the time required for instancing operations.
2Reliability
If the entire simulation is re-run for each scene modification, then the simulation results remain accurate, but the resource consumption (data storage, processing power) increases
Solution Approach 1:
The global simulation is segmented into independent local simulations that can be stored and reused. Instead of re-running the entire simulation, only the necessary local segments are retrieved and combined. This approach maintains result reliability while significantly reducing computational resource usage, as the expensive global computation is performed only once during the pre-computation phase.
Solution Approach 2:
The patent creates copies of pre-computed local simulation results that can be reused across multiple instancing operations. These copies store the essential simulation data in a condensed form that can be quickly retrieved and combined, maintaining reliability while avoiding the need to re-execute the full simulation and thus reducing resource consumption.
3Area of stationary object
If traditional instancing methods are used for large-scale simulations, then complete scene coverage is achieved, but the computational cost grows exponentially with scene size
Solution Approach 1:
The large-scale simulation domain is divided into multiple smaller local simulations or zones of interest. Each local simulation can be independently computed, stored, and reused. When instancing is required, the system retrieves only the relevant local simulations needed for the current scene configuration, rather than re-computing the entire large-scale simulation. This segmentation enables efficient instancing while maintaining complete scene coverage.
Solution Approach 2:
Instead of computing the entire global simulation, the system performs partial computations by pre-calculating only the necessary local simulations. This partial action approach computes less than the full global simulation but provides sufficient information for instancing, thereby improving productivity while still achieving complete scene coverage through strategic combination of local results.
Data Source
AI summary
The disclosure notably relates to a computer-implemented method for instancing a global physics simulation. The method includes obtaining a set of local simulations. The set of local simulations includes at least one local simulation. A local simulation is a physics simulation that is part of the global physics simulation and that can be computed alone and independently of the global physics simulation. Each local simulation of the set of local simulations is already computed. The method further includes, for each local simulation of the set of local simulations, computing a respective reduced model of the local simulation. The method further includes computing each global simulation of a set of at least one global simulation. Each global simulation is an instance of the global physics simulation. This constitutes an improved method for instancing a physics simulation.