How Does A Changing Automotive Ecosystem Affect Tier-1 Suppliers?


Tier-1 automotive suppliers have an enormous opportunity in the development of autonomous vehicles (AVs). Fortune.com sees these vehicles contributing $7 trillion in economic activity by the year 2050. But this opportunity comes with a challenge: the whole supply chain is being disrupted by new participants and new technologies that are making these AVs possible. Semiconductor companies and spe... » read more

Emulation Fills The Pre-Silicon Verification Gap For Autonomous Vehicles


Veloce emulators provide the scale and performance to ensure that automotive applications run smoothly, safely, and securely. This paper describes how emulation is used to run realistic driver scenarios, investigate vehicle dynamics, and analyze power and communications metrics — all in a platform that virtualizes the design and allows both hardware and software to be tested together or separ... » read more

Which Verification Engine When


Frank Schirrmeister, group director for product marketing at Cadence, talks about which tools get used throughout the design flow, from architecture to simulation, formal verification, emulation, prototyping all the way to production, how the cloud has impacted the direction of the flow, and how machine learning will impact verification. » read more

5G Needs Cohesive Pre- And Post-Silicon Verification


While 5G doesn’t start from a clean slate, it does make significant changes to the 4G architecture. These changes mean that the ecosystem from chips to operators is evolving, giving opportunities to more companies to engage in this growing market. Realignment in fronthaul, midhaul and backhaul In particular, the radio access network (RAN) has been redefined as Cloud RAN (sometimes called ... » read more

5G Verification Is Impossible Without Emulation


Emulation, combined with a rich assortment of virtualized versions of the many protocols that 5G will require, is the only practical way of ensuring that the first round of silicon built will be the production version, able to handle all of the functions and configurations that it might be faced with and having the tight performance characteristics needed for successful integration into a 5G sy... » read more

Focus Shifts To Wasted Power


Mobile phones made the industry aware of power, but now the focus is shifting to the total energy needed to perform a task. Activity that is unnecessary to perform the intended task is wasted power, and reducing it requires some new methodologies and structural changes within development teams. There is a broadening awareness about power. "The companies doing SoCs for mobile lead the charge ... » read more

Using Emulators For Power/Performance Tradeoffs


Emulation is becoming the tool of choice for power and performance tradeoffs, scaling to almost unlimited capacity for complex chips used in data centers, AI/ML systems and smart phones. While emulation has long been viewed as an important but expensive asset for chipmakers trying to verify and debug chips, it is now viewed as an essential component for design optimization and analysis much ... » read more

The Race For Better Computational Software


Anirudh Devgan, president of Cadence, sat down with Semiconductor Engineering to talk about computational software, why it's so critical at the edge and in AI systems, and where the big changes are across the semiconductor industry. What follows are excerpts of that conversation. SE: There is no consistent approach to how data will be processed at the edge, in part because there is no consis... » read more

Debug Tools Are Improving


Semiconductor Engineering sat down to discuss debugging complex SoCs with Randy Fish, vice president of strategic accounts and partnerships for UltraSoC; Larry Melling, product management director for Cadence; Mark Olen, senior product marketing manager for Mentor, a Siemens Business; and Dominik Strasser, vice president of engineering for OneSpin Solutions. Part one can be found here. Part two... » read more

Optimizing Power For Learning At The Edge


Learning on the edge is seen as one of the Holy Grails of machine learning, but today even the cloud is struggling to get computation done using reasonable amounts of power. Power is the great enabler—or limiter—of the technology, and the industry is beginning to respond. "Power is like an inverse pyramid problem," says Johannes Stahl, senior director of product marketing at Synopsys. "T... » read more

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