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Design007-Dec2021

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38 DESIGN007 MAGAZINE I DECEMBER 2021 performance and manufacturability, or SI and thermal performance). Today, the state-of-the-art is multi-physics simulators (e.g., SI and PI, PI and thermal, thermal and vibration) coupled with AI- enabled technologies capable of identifying the ideal solution given a set of target operat- ing parameters. Cloud-based compute farms promise scalability from today's world where, even within one discipline like SI, only small portions of the system model can be analyzed at a time. As there are oen far too many manual steps and opportunities for error and wasted time, there are efforts to streamline the digital thread from the core design database and authoring environment into these simu- lators. Yet we're still a ways off from the holy grail of a single, multi-dimensional model of the product that's consumed by a single, multi- dimensional simulator capable of emulating all real-world conditions. I should note that, while many simulators have been validated in comparison to a physical prototype, the real target is the product in use in its end-market. at environment doesn't have test fixtures that artificially send signals, nor does it have mechanical jigs that hold a single board in a HALT chamber. Simulators can test corner cases on a digital twin—something that's impractical with physical prototypes (even if you build thousands of boards, you can't ensure that they represent every possible operating condition). And simulators offer the promise of automated multi-domain verification vs. the one-at-a-time manual testing processes for physical prototypes. Over the past couple decades, verification has been slowly shiing earlier (to the le) in the design process. It moved first from a physical prototype-only approach to complex, hard-to-use simulators applied at the end of the design process by domain specialists. e second shi in verification has been from the end of design to the core authoring stage, enabled by tighter integration with the central digital twin of the design. While not replacing interconnects. Since models are necessary for an array of checks, they must also be multi- discipline. For instance, a PCB component model could be used to verify signal integrity (SI), power integrity (PI), thermal, form/fit, vibration, and more. Today, while there are more models for PCB components than any other part of the electronics system, they are still far from ideal: there are multiple formats (e.g., IBIS, VHDL- AMS, BCI-ROM); there are many variants, each targeted at a single type of analysis; and quality varies widely. Yet, there is hope. Device vendors realize the value of models to help sell their product, so some are introducing models when they launch a new device. And there are industry efforts to standardize on neutral formats to represent multi-discipline models. In the meantime, creation and/or validation of models is oen le to each engineering team that wants to utilize them. If digital twins (models) are the fuel, then the simulators that consume them are the engine. ese engines typically perform a single function (e.g., SI analysis, or even more specifically, DDRx or SerDes analysis). Significant energy has been spent over the last two decades to improve the accuracy of these simulations so that they mirror what's seen in the real world with the physical product. Of course, it's a moving target, as new signaling protocols are introduced along with new devices, materials, and manufacturing processes. Since the results of these simulations are typically one-dimensional, it's le to the engineer to manage trade-offs (e.g., between If digital twins (models) are the fuel, then the simulators that consume them are the engine.

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