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Complexity is driving the urgency for advanced artificial intelligence systems more than ever—and that means someone has to supply the tools to create those systems. Cadence is up to the task: we’ve been expanding our AI offerings. If you haven’t already seen what Cadence can do for your AI needs, or if you’re not quite up-to-date on this whole AI boom, let this presentation given by K.T. Moore at the Cadence Theater at DAC bring you up to speed.
The technology behind AI isn’t as new as you’d think—the principles that govern how AI learns have been in development since 1959, when Arthur Samuel defined the concept of “machine learning.” At the time, there was nothing even resembling the necessary compute power to put Samuel’s concepts into practice—but now we can. AI designs are huge, and they’re massively parallel—simulating them on older computers and simulators would have taken ages; never mind how long it would take to do some by-hand measure like they had to do in the '60s.
But with advancements in server technology and the parallelization technology in products like Xcelium Parallel Logic Simulator and JasperGold smart technology, plus hardware-based engines like the Palladium and Protium platforms, verifying AI designs is not only possible—it’s easy. But, read on, its not just about simulation technology.
AI tech is flooding the industry. It’s applicable to almost every vertical—cloud computing can use AI to intelligently manage a user’s required resources, consumer electronics are using it to tailor a user experience based on a whole host of collected data, automotive companies want to use AI to drive cars, healthcare to assist in diagnoses given a set of symptoms and a database of other, similar patients—and that’s saying nothing of the multitude of industrial applications. AI is also useful in the creation of developers’ tools themselves. Part of what’s causing the semiconductor industry boom is just this—an exploding interest in AI chips. And with 5G technology imminent, and with the looming billion-gate plus sizes of the SoCs that implement 5G, AI-assisted developers' tools might need to become the norm, not an outlier.
So: in all of this, where is Cadence?
Cadence is focusing its efforts on two areas, dubbed “machine learning inside” and “machine learning outside.” ML inside in the digital design flow refers to improving PPA, faster engines, and better testing and diagnostics. None of this physically affects how you use a tool, but it makes using that tool a much better experience. ML outside talks about the design flow in general, working toward an automated design flow, as well as productivity improvements across the flow. These things do change how you use a tool, but don’t worry, it’s all for the better.
Additionally, Cadence is working to improve design enablement; that is, hardware and software co-design. Smart Genus and Innovus solutions make designing your SoC easier than ever—using the full flow can result in up to a 21% PPA gain.
If you’re looking specifically for IP to enable AI on your SoC, the Tensilica DNA 100 processor has you covered, too. It’s great for companies designing edge or AI chips, offers great compression rates and efficient power usage, and has 4.7X the performance of other AI SoC IP on similar array sizes.
Cadence has you covered no matter where you’re going in this new world of AI systems—with our AI-enabled tools, IP, and our strong partner ecosystem, you can be at ease knowing you’ll be supported no matter how complex your needs are.