Adaptive Circuit Design Flows for Faster EDA Iteration
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Solution Overview
Problem
Existing electronic design automation (EDA) tools lack the ability to adaptively and incrementally improve circuit design processes, leading to inefficient and resource-intensive iterations due to the lack of learning from prior runs and one-size-fits-all approaches that do not scale across different circuit blocks.
Innovation Solution
Implementing a self-guided flow component that dynamically adjusts design processes based on learning from previous runs, using machine learning models to analyze health metrics and make intelligent recommendations for placement, routing, and optimization, and employing subflows to explore interactions between subsystems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional EDA tools use fixed predefined flows for circuit design, then the process is simple to implement, but the system cannot adapt to different circuit blocks and requires extensive manual tuning
Solution Approach 1:
The patent implements dynamic flows that can adapt and change based on circuit characteristics. The system transitions from fixed predefined flows to dynamic flows that are generated and adjusted during the design process, allowing the EDA tool to adapt to different circuit blocks automatically without manual intervention.
Solution Approach 2:
The system performs self-guided flow generation and self-tuning by automatically analyzing circuit characteristics and generating appropriate design flows without requiring manual expert intervention. The EDA tool serves itself by autonomously adapting to different circuit blocks.
2Manufacturing precision
If manual tuning and iteration are performed to optimize power, performance, and area, then design quality improves, but turnaround time and resource consumption increase significantly
Solution Approach 1:
The system performs preliminary analysis of circuit characteristics before the main design process, generating appropriate flows in advance. This preliminary action allows the system to avoid extensive manual tuning and iteration during the actual design process, significantly reducing turnaround time while maintaining design quality.
Solution Approach 2:
The system implements feedback mechanisms where design results and metrics are continuously monitored and used to adjust the design flow dynamically. This feedback loop enables automatic optimization of power, performance, and area without requiring multiple manual iteration cycles, reducing both time and resource consumption.
3Reliability
If extensive iterations and manual tuning are performed, then optimal design results are achieved, but engineer resources and machine resources are consumed excessively
Solution Approach 1:
The system performs self-guided optimization by automatically analyzing design metrics and adjusting parameters without requiring extensive manual engineer intervention. This self-service capability maintains design optimization quality while significantly reducing both human and machine resource consumption.
Solution Approach 2:
The system dynamically changes design parameters and flow configurations based on circuit characteristics and design metrics. By automatically adjusting parameters rather than performing extensive manual iterations, the system achieves optimal design results with reduced resource consumption.
4Productivity
If a one-size-fits-all approach is used across different circuit blocks, then the system is simple to manage, but it does not scale and requires tool tuning for each block
Solution Approach 1:
The patent implements dynamic flows that automatically adapt to different circuit blocks based on their characteristics. This dynamic approach enables the system to scale across diverse circuit blocks without requiring manual tuning for each block, significantly improving productivity while managing complexity through automation.
Solution Approach 2:
The system segments the design flow into modular components that can be independently configured and executed based on circuit characteristics. This segmentation allows the system to handle different circuit blocks efficiently without requiring complete reconfiguration, improving scalability while maintaining manageable system complexity.
Data Source
AI summary
Certain aspects of the present disclosure are directed towards a method for circuit design processing. The method generally includes: performing, via a first processing unit, a first stage of a design process for a circuit design; collecting data associated with processing at least a portion of the circuit design via the first processing unit; providing at least a portion of the collected data to a second processing unit to perform a second stage of the design process for at least the portion of the circuit design to yield a circuit processing result; and providing the circuit processing result to the first processing unit to aid in performing the first stage of the design process.