SpyGlass-CDC: Combining Structural And Functional Verification Techniques

How to improve effective clock domain crossing verification and how it can save big bucks in redesign costs.

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Multiple, independent clocks are quintessential in SoCs and other complex ASICs today. In some cases, such as in large communications processors, clock domains may number in the hundreds. Clock domain crossings pose a growing challenge to chip designers, and constitute a major source of design errors–errors that can easily slip past conventional verification tools and make their way into silicon.

When these errors make it into silicon, the costs are high. A single silicon re-spin may cost $10 million and extend time-to-market by months, greatly reducing the chip’s market share and profit potential. Even if caught prior to silicon in the late stages of design, a bug may still run up $100,000 or more in redesign costs.

Therefore, there is a substantial benefit to identifying and correcting CDC problems in the early stages of the design, at the RTL level, when corrections may be made quickly and at minimal cost (a few hundreds or thousands of dollars). Unfortunately, cycle-based simulation, the mainstay of RTL-stage verification, is not well suited to finding and tracing timing-related errors resulting from CDC problems. Static timing analysis tools treat clock domain crossings as exceptions and ignore them.

Furthermore, traditional structural CDC analysis tools can help identify clock domain crossings and perform some basic synchronization checking, but none offers the kind of comprehensiveness or precision users require. Such tools tend to simultaneously overlook a number of real design errors and over-report a large numbers of false violations. The CDC problem therefore calls for next-generation tools that provide more advanced CDC verification.

Such tools must look at the architecture of complex data transfers across clock domains and combine a number of techniques–including both structural analysis and functional, assertion-based checks. Only in this way can new tools provide the completeness and accuracy that CDC verification demands. To download the white paper on how to address these demands, click here.


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