In both data centers and automobiles deep learning is taking hold. But it is a technique that challenges conventional microprocessors, leading system designers to look at alternative architectures for acceleration.
A technique built for software development is now helping hardware engineers master increasingly complex verification flows.
How the powertrain of an electric vehicle is modeled first in software, then elaborated using virtual hardware running target code, to enable virtual FMEA with rich data-gathering and analysis capabilities.
Static analysis offers a powerful way of identifying potential X-optimism problems before simulation. The article defines the issue and describes an established solution.
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