Smarter, Faster, Leaner: Rethinking Verification For The Modern Era

Verification isn’t just another step in the semiconductor design process—it’s increasingly the step that defines whether teams hit their schedules or miss the mark. With skyrocketing design complexity, accelerated development timelines, and persistent engineering shortages, the industry is feeling the pressure. Traditional methods aren’t keeping pace.

At Siemens, we’ve been rethinking how verification should work in this new environment. Earlier this year, we proposed a different path forward in Breaking the Bottleneck—a call for smarter, scalable, and more connected verification. That idea has now moved from concept to practice through the development of the Questa One smart verification solution, which reflects our response to the shifting needs of modern design teams.

The result is a set of technologies that prioritize intelligence, integration, and adaptability—engineered to help teams keep up with both the scale and pace of modern silicon development.

Connecting the dots across engines and teams

One of the long-standing challenges in verification is fragmentation. Simulation, static analysis, formal methods, and debug often run in parallel, but rarely in unison. That disjointedness adds overhead, slows iteration, and increases the chance of gaps slipping through the cracks.

The industry is shifting toward more unified approaches—where simulation, formal, and static engines work together in concert. When verification workflows also integrate with test solutions and hardware acceleration platforms, teams gain a clearer path from RTL to full-system coverage. Centralized debug environments and shared data views further help align global teams around a single source of truth.

Turning data into action

More data is being generated during verification than ever before—but simply having data isn’t enough. What matters is transforming it into insight.

Modern verification solutions are embedding AI and analytics directly into the flow to surface actionable information. That includes identifying failure patterns, prioritizing high-risk tests, highlighting root causes, and even generating assertions using generative AI. These capabilities shift the role of engineers from putting out fires to optimization, helping teams spot issues earlier and focus resources where they’ll have the biggest impact.

More than just enhancing individual tools, AI is increasingly orchestrating the entire verification flow—learning from patterns, coordinating decisions across engines, and helping teams move from reactive debugging to proactive closure.

By moving from reactive to predictive workflows, verification becomes not just faster—but smarter.

Scaling for modern complexity

The days of verifying a full SoC on a single workstation are long gone. Today’s designs span far more than RTL—they often include 3D ICs and chiplets, which increase complexity through cross-die interactions, power and thermal concerns, and expanded system-level test requirements. Add in software-driven behavior and stringent safety constraints, and verification becomes a truly multidimensional challenge.

Scalability isn’t just about performance anymore. It’s about flexibility—adapting compute usage based on workload, user role, or phase of the project. Whether in the cloud or on-prem, simulation and formal engines must scale horizontally across compute clusters and work seamlessly with orchestration frameworks to make the most of available resources.

We’ve seen that when infrastructure can scale intelligently, verification bottlenecks can turn into opportunities for acceleration—from regression throughput and fault analysis to design-for-test (DFT) validation.

Real-world impact

Teams adopting these new approaches are already seeing significant results:

• A global electronics company cut DFT closure from weeks to days by accelerating pattern simulation and sign-off with more integrated flows.
• A leading processor IP provider boosted regression throughput by 43% while improving cloud efficiency.
• A top-tier chipmaker slashed fault simulation time from over four hours to under five minutes using accelerated analysis combined with automated diagnostics.

These aren’t marginal improvements—they’re transformative shifts in how verification gets done.

The road ahead

Once considered a technical checkpoint, verification is now a primary factor in project success. It influences everything from time-to-market to silicon quality—and ultimately, business outcomes. But the traditional ways of verifying designs—isolated tools, manual processes, and compute-constrained workflows—just don’t cut it.

That’s why we’ve built our latest verification solution around three core principles: connected, data-driven, and scalable. Our smart verification solution—anchored by the Questa One smart verification solution—embeds AI across the flow, connects siloed processes, and scales from block-level validation to full-system sign-off.

As designs get more complex and teams more distributed, success will hinge on how well verification can adapt. The industry needs solutions that make engineers faster, verification cycles leaner, and debug more targeted.

Smarter verification isn’t a future vision anymore—it’s today’s reality. Verification may be the biggest challenge in semiconductor design—but with the right approach, it’s also our biggest opportunity for transformation.

For a deeper look at how Siemens is making this vision real, read the whitepaper: Turning Vision into Reality: How Questa One Fulfills the Promise of Smart Verification.