Aging Visibility for Long-Term Clock Reliability

vAging delivers SPICE-accurate analysis of how clock paths degrade over time and how these changes affect long-term timing integrity.

It models BTI and HCI degradation under real activity patterns and reveals aging-induced delay growth, asymmetric degradation, duty-cycle distortion, and loss of edge quality that existing methodologies cannot accurately predict.

vAging uses a Fresh, Stress, Aging simulation flow at transistor-level fidelity to track degradation across the full clock domain, including multi-million gate meshes, trees, and hybrids.

With vHelm, designers can explore what-if scenarios and apply Virtual ECO adjustments to test parking strategies, stress conditions, and design fixes with immediate waveform accuracy.

Teams gain long-term visibility into how their clocks will behave in the field and can protect performance, reliability, and margin throughout the product lifetime.

Aging Effects That Threaten Clock Stability

At advanced nodes, aging has become one of the most underestimated risks to clock integrity and product performance. Aging-driven clock failures are not just silicon issues. In high-volume markets they can trigger product recalls, customer dissatisfaction, and long-term damage to business credibility. Accurate aging prediction protects not only the design, but the company behind it.

BTI and HCI shift device thresholds over time, slowing clock paths and degrading edge quality in ways that compound across billions of cycles. These effects intensify under real workloads where clock-gating patterns, voltage variation, and temperature gradients create uneven, asymmetric aging that static margins and simplified stress assumptions cannot capture. When these interactions go unseen, entire classes of failures escape detection until silicon is already in the field.

vAging exposes these degradation mechanisms directly and shows how delay, duty cycle, and slew evolve under real operating conditions. Designers can pinpoint aging hot spots early, validate mitigation strategies, and prevent long-term failures well before sign-off.