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How to utilize long slack in critical path analysis? 


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To utilize long slack in critical path analysis, various methods can be employed. One approach involves timing slack optimization through a hybrid routing strategy like rip-up-retry and pathfinder, which adjusts critical paths detouring long distances to reduce critical path delays and optimize path slack . Another method includes implementing downstream slack creation in paths immediately following the critical path, followed by slack stealing to enhance the critical path's timing based on the downstream slack generated . Additionally, an on-chip timing slack monitor can be utilized to measure timing slack at the end of a critical path, providing valuable data for yield analysis and decision-making . Incorporating in-situ slack monitors in functional paths can also help manage wear-out and minimize margins related to manufacturing variations and operating conditions .

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Zero-slack, noncritical paths challenge traditional critical path analysis by highlighting the importance of considering paths with slack for optimal project duration reduction strategies.
Utilize long slack in critical path analysis by selecting endpoint registers strategically based on timing analysis, considering stochastic dispersion, aging, process variations, and temperature effects for efficient monitor insertion.
Patent
27 Dec 2013
7 Citations
Utilize an on-chip timing slack monitor with a master-slave flip-flop, logic module, and pulse width shrinking delay line for measuring and analyzing timing path slack in critical path analysis.
Slack stealing is used to improve critical path timing by creating downstream slack in the next cycle and utilizing it for timing optimization in integrated circuit development.

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In what year was the Slack Variable model first announced?5 answersThe Slack Variable model was first introduced in the field of control systems by Holloway in 1993. This model was developed to address uncertainties in dynamic systems and observation costs, providing a framework for controlling systems subject to model or input uncertainties. Additionally, the concept of slack variables was later applied to receding horizon control with inequality constraints by Hiroki, who described its formulation in the context of swing leg dynamics. The use of slack variables in these contexts allowed for more robust and flexible control strategies, enabling the handling of complex systems with varying constraints effectively.
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