Wally Rhines, president and CEO of Mentor, a Siemens Business, sat down with Semiconductor Engineering to discuss a wide range of industry and technology changes and how that will play out over the next few years. What follows are excerpts of that conversation. SE: What will happen in the end markets? Rhines: The end markets are perhaps more exciting from a design perspective right now than they have been in recent years. Everyone is intrigued with the electronic design opportunities that have been emerging in the automotive industry.
Verified artificial intelligence (AI) is the goal of designing AI-based systems that are provably correct with respect to mathematically-specified requirements. This paper considers Verified AI from a formal methods perspective. We describe five challenges for achieving Verified AI, and five corresponding principles for addressing these challenges.
The growth of artificial intelligence (AI) demands that semiconductor companies re-architect their system on chip (SoC) designs to provide more scalable levels of performance, flexibility, efficiency, and integration. From the edge to data centers, AI applications require a rethink of memory structures, the numbers and types of heterogeneous processors and hardware accelerators, and careful consideration of how the dataflow is enabled and managed between the various high-performance IP blocks. This paper will define AI, describe its applications, the problems it presents, and how designers can address those problems through new and holistic approaches to SoC and network on chip (NoC) design. It also describes challenges implementing AI functionality in automotive SoCs with ISO 26262 functional safety requirements.
While self-driving vehicles are beta-tested on some public roads in real traffic situations, the semiconductor and automotive industries are still getting a grip on how to test and verify that vehicle electronics systems work as expected. Testing can be high stakes, especially when done in public. Some of the predictions about how humans will interact with autonomous vehicles (AVs) on public roads are already coming true, but human creativity is endless. There have been attacks on Waymo test vehicles in Arizona, a DUI arrest of a Tesla driver sleeping at 70mph on a freeway, and other Tesla hacks using oranges and aftermarket gadgets to trick Tesla's Autopilot into thinking the driver's hands are on the wheel. But are those unsafe human behaviors any more dangerous than the drum beat of technology hype, unrealistic marketing, and a lack of teeth in regulating testing of AVs on public roads, the factory and the design lab?
The industry and users have a love/hate relationship with UVM. It has quickly risen to become the most used verification methodology and yet at the same time it is seen as being overly complex, unwieldy and difficult to learn. The third day of DAC gets started with breakfast with Accellera to discuss UVM and what we can expect to see in the next 5 years. The discussion was led by Tom Alsop, principle engineer at Intel. Alsop's first question to the panelists was, where do you see UVM in the next 5 years?