Design Component Tuning for IC Yield and Power Optimization
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Solution Overview
Problem
Current manufacturing techniques for devices like integrated circuits face challenges in achieving optimal performance, yield, and cost efficiency due to the trade-offs between device speed, area, and power consumption, with existing methods often resulting in over-design that increases sensitivity to yield loss and reduces production throughput.
Innovation Solution
A method that optimizes device design by tuning both design components and manufacturing technology to reduce variability, allowing for co-optimization of multiple parameters such as device speed, power consumption, and area, while considering the effects of manufacturing processes on critical and non-critical paths, using techniques like lithographic processing to enhance the process window and select appropriate design components from a library.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If design components are selected to be too fast to guarantee meeting speed requirements under manufacturing variation, then device speed requirement is satisfied, but power consumption and area increase
Solution Approach 1:
The patent applies parameter changes by adjusting manufacturing process parameters (such as lithographic settings, etch conditions, deposition parameters) to control and reduce variability in design component characteristics. This allows selecting components that meet speed requirements without excessive margin, thereby reducing power consumption and area while still satisfying performance specifications under manufacturing variation.
2Reliability
If design components are selected to be too fast to guarantee meeting speed requirements under manufacturing variation, then device speed requirement is satisfied, but device area increases
Solution Approach 1:
The patent uses parameter changes in manufacturing processes to reduce variability in component dimensions and electrical characteristics. This enables more precise selection of smaller-area components that will still meet speed requirements after manufacturing, thereby reducing overall device area while maintaining reliability.
3Reliability
If overall variability for the whole library is reduced to increase yield, then manufacturing yield improves, but design becomes more sensitive to other yield loss sources and power consumption increases
Solution Approach 1:
The patent applies local quality by focusing variability reduction efforts on specific critical design components and critical paths rather than uniformly reducing variability across the entire library. This targeted approach improves yield for the most sensitive components without unnecessarily increasing power consumption in non-critical areas, achieving better overall efficiency.
Solution Approach 2:
The patent uses parameter changes in manufacturing processes to achieve selective variability control for critical components. By adjusting process parameters specifically for critical paths, the patent improves yield where it matters most without requiring across-the-board variability reduction that would increase power consumption.
4Reliability
If over-design is used to guarantee meeting requirements under manufacturing variation, then reliability is improved, but production throughput decreases
Solution Approach 1:
The patent applies parameter changes in manufacturing processes to reduce variability in component characteristics. This enables selection of components that meet requirements without excessive over-design margin, allowing faster operation and higher production throughput while still satisfying specifications under manufacturing variation.
Data Source
AI summary
A method for optimizing a design for a device is disclosed. Such an optimization is performed with respect to a predetermined metric, e.g. device speed, area, power consumption or yield. In one aspect, the method comprises obtaining a design for a device. The design comprises design components. The method also comprises determining from the design components at least one group of first design components that has a higher sensitivity to the predetermined metric than second design components. The first design components may be on the critical path in the design. The method further comprises tuning the first design components and the technology for manufacturing the first design components thus reducing the variability of the first design components and obtaining an optimized design with respect to the predetermined metric.