Abstract
Aggressive technology scaling and ultra low power constraints have resulted in less predictable device behavior complicating timing analysis/estimation. The traditional delay models fail to accurately capture the circuit behavior under such conditions. This paper proposes a novel highly accurate Inverse Gaussian Distribution (IGD) based delay model applicable to both combinational and sequential elements for sub-powered circuits. The IGD based delay estimation accuracy is demonstrated by evaluating multiple circuits, i.e., D Flip Flops (DFFs) + 8-bit Ripple Carry Adder, and 8-bit De-multiplexer (DEMUX) and Multiplexer (MUX). Our experiments indicate that the IGD based approach provides a high matching against HSPICE Monte Carlo simulation results, with an average error less than 1.9% and 1.2% for the two circuits, respectively, while sparing orders of magnitude simulation time. Moreover, the IGD model outperforms the traditional Gaussian Distribution (GD) model by providing 6 × better average accuracy with no extra simulation time overhead.
| Original language | English |
|---|---|
| Pages (from-to) | 2754-2761 |
| Number of pages | 8 |
| Journal | Microelectronics Reliability |
| Volume | 55 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 1 Dec 2015 |
Keywords
- CMOS process variations
- Delay model
- Near/sub-threshold operation
- Statistical modeling
- Timing analysis
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