Automated HDL Code Generation for Frame-Based Processing
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Solution Overview
Problem
The process of translating graphical models into hardware implementations is computationally intensive and often requires manual optimization of hardware description languages (HDL) for frame-based processing, which can be complex and time-consuming, especially when balancing hardware size and latency requirements.
Innovation Solution
An automated method for generating HDL code from graphical models that allows users to select options for HDL generation based on target hardware size and latency, with the option to automatically analyze and optimize hardware implementations, enabling efficient frame-based processing by determining the best implementation strategy for each block and potentially parallelizing or serializing operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual optimization of HDL code is performed for frame-based processing, then hardware implementation precision is improved, but device complexity and time consumption increase
Solution Approach 1:
The system performs self-service by automatically generating optimized HDL code from graphical models without requiring manual intervention. The code generation application analyzes the frame-based processing requirements and produces optimized hardware description language code autonomously, eliminating the need for manual HDL optimization while maintaining high implementation precision.
Solution Approach 2:
The patent replaces the manual mechanical process of HDL code optimization with an automated computational system. The code generation application uses algorithmic processing to transform graphical models into optimized HDL code, substituting human expert manual work with an automated software-based mechanism that achieves the same or better results without the associated complexity and time costs.
2Manufacturing precision
If manual optimization of HDL code is performed, then hardware implementation quality is improved, but time consumption increases
Solution Approach 1:
The system performs preliminary action by automatically generating optimized HDL code during the design phase from graphical models. The code generation application prepares the hardware description language code in advance with built-in optimizations for frame-based processing, eliminating the need for subsequent manual optimization time while ensuring high implementation quality.
Solution Approach 2:
The code generation application provides self-service by autonomously producing optimized HDL code without requiring manual intervention. The system automatically analyzes the graphical model, determines optimal hardware implementation strategies, and generates ready-to-use HDL code, significantly reducing the time consumption associated with manual optimization processes.
3Ease of operation
If automated HDL generation is implemented, then ease of operation is improved, but manufacturing precision may worsen without proper optimization
Solution Approach 1:
The code generation application performs self-service by automatically applying optimization algorithms to the generated HDL code. The system not only generates code from graphical models but also autonomously optimizes it for frame-based processing, ensuring high manufacturing precision is maintained while preserving the ease of operation provided by automated generation.
Solution Approach 2:
The system implements feedback by analyzing the generated HDL code and automatically applying optimizations based on frame-based processing requirements. The code generation application evaluates the generated code and iteratively improves it, ensuring that manufacturing precision is maintained or enhanced while keeping the operation automated and easy to use.
Data Source
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AI summary
An automatic code generation application is used to automatically generate code and build programs from a textual model or graphical model for implementation on the computational platform based on the design. One or more model elements may be capable of frame-based data processing. Various options and optimizations are used to generate Hardware Description Language (HDL) code for the frame-based model elements.