Graphical Modeling Environment for Automatic Functional Mapping

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing technical computing environments lack efficient methods for optimizing the mapping of functional models onto diverse architectural models, particularly in distributed embedded and parallel computing systems, which hinders the effective utilization of various processing and input/output devices.

Innovation Solution

A graphical modeling environment (GME) that generates functional effect information by mapping functional models to architectural models, considering types of processing and input/output devices, communication pathways, and device drivers, allowing for simulation and code generation to identify optimal mappings and architectures.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual mapping of functional models to architectural models is performed, then mapping accuracy can be ensured, but time consumption and complexity increase significantly

Engineering Contradiction:

Improvemapping accuracyVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system enables automatic mapping where the computational environment autonomously maps functional model elements to architectural model elements without requiring manual user intervention. The mapping process is performed automatically by the system based on predefined rules and algorithms, significantly reducing time consumption while maintaining acceptable mapping accuracy.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system allows dynamic adjustment of mapping parameters and criteria to optimize the balance between mapping accuracy and automation level. Users can configure different mapping strategies and parameters depending on their specific needs, enabling the system to adapt between more automatic or more precise mapping approaches as required.

Inventive Principle:

Principle #35Parameter changes

2Productivity

If automatic mapping is implemented, then productivity increases, but mapping precision and control decrease

Engineering Contradiction:

Improvemodeling efficiencyVSAvoidmapping precision

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system incorporates feedback mechanisms that allow users to review and validate automatic mapping results. The mapping process can be iteratively refined based on user feedback, enabling the system to learn from corrections and improve future automatic mapping precision while maintaining high productivity.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system implements a hybrid approach where critical mapping elements are automatically mapped with high precision, while less critical elements use faster automatic mapping. This partial automation strategy maintains overall mapping precision for important components while achieving high productivity across the entire model.

Inventive Principle:

Principle #16Partial or excessive action

3Adaptability or versatility

If comprehensive architectural models with multiple processing devices are used, then system capability and versatility improve, but device complexity and difficulty of management increase

Engineering Contradiction:

Improvesystem capabilityVSAvoidarchitectural complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system segments the complex architectural model into manageable components and elements that can be independently configured and managed. By dividing the architectural model into modular components, the system enables comprehensive system capability while reducing the perceived complexity through structured organization and hierarchical management.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system implements universal mapping mechanisms that can handle multiple types of processing devices and architectural configurations through a common framework. This multi-functional approach allows the system to support diverse device types and complex architectures without requiring separate management procedures for each case, thereby reducing operational complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Measurement precision

If detailed functional models are created to ensure accuracy, then model precision improves, but the complexity of model creation and maintenance increases

Engineering Contradiction:

Improvefunctional model accuracyVSAvoidmodel creation complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system performs preliminary automatic mapping and validation of functional models before detailed implementation. By conducting initial mapping and accuracy checks in advance, the system ensures functional model accuracy is established early, reducing the need for complex iterative adjustments and simplifying subsequent model maintenance.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS9558305B1Automatic modeling, mapping, and code generation for homogeneous and heterogeneous platforms

Publication Date: 2017.01.31 MATHWORKS INC

AI summary

In an embodiment, a system may receive information regarding a group of physical devices; receive information regarding a set of functional blocks associated with a functional model; and receive mapping information that indicates a mapping between the set of functional blocks and one or more physical devices of the group of physical devices. The system may further generate at least one functional effect associated with the functional model. The generating may be based on: the set of functional blocks, the mapping information, and the information regarding the one or more physical devices. The system may also store or output the at least one functional effect.