π€ Exploring Chip Variation Models β OCV, AOCV, & POCV π
π―The evolution of chip variation models from OCV (On-Chip Variation) to AOCV (Advanced On-Chip Variation) and POCV (Parametric On-Chip Variation).
π Newer models have emerged, how they surpass their predecessors, and their impact on reducing timing pessimism in chip design.
π Systematic Variation: Predictable and modifiable as technology advances.
π Random Variation: Unpredictable and challenging to model, typically managed by applying a derate factor to cell delays.
π§ Why Adjust Models?
To prevent timing failures post-fabrication, it's crucial to consider potential process variations during the Static Timing Analysis (STA). Here's how different models handle this:
βOCV Approach: Applies a fixed timing derate across all cells. This broad application can often be overly pessimistic.
% set_timing_derate -cell_delay-rise -data -early 0.92 % set_timing_derate -cell_delay-rise -data -late 1.10
βAOCV Enhancements: Introduces variability in derate factors based on cell type, path depth, and distance, reducing overall pessimism and improving timing accuracy.
β POCV Innovations: Moves away from fixed derate factors, using a statistical approach based on normal distribution of cell delays to refine the modeling further.
π Moving Forward:
As technology nodes shrink below 40nm, the precision of these models becomes even more critical. POCV, for instance, offers significant advantages in high-frequency designs by minimizing slack pessimism and enhancing model realism.
π Want to understand more with detailed explanations join our 3 week STA BootCamp, contact to avail discount and book -
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