AI for Chip Design Verification
By Lauro Rizzatti, EE Web
It’s an exciting time for anyone in the chip and electronic design automation (EDA) industry, asserts Dr. Raik Brinkmann, president and CEO of formal verification provider OneSpin. Dr. Brinkmann uses new computer architectures, breaking the Von Neuman principle and pushing computing to a different level as an example, and says that they offer an opportunity for agile EDA companies with significant technology portfolios.
Artificial intelligence (AI), however, captures Dr. Brinkmann’s imagination, and he is studying what it can do to help design and verify chips. Implementing AI applications on hardware, he begins, involves mapping algorithms developed for AI into a hardware platform that could be an ASIC, an FPGA, a DSP, or one that’s more sophisticated. Each has a verification challenge: verifying the algorithm.
Once engineers have decided on a platform and architecture, they usually trust the implementation flow and platform, though sometimes a more rigorous approach is required, such as targeting safety-relevant applications through AI algorithms. They may use specific verification techniques for the algorithm itself. The challenge is to pick the right platform for the application.
An AI platform consists of a general-purpose processor that is used to manage the data and administer all of the types of computation that it needs to perform. Some accelerators are specific to an application; others can be more generic and support a variety of applications. A memory subsystem and a set of input/outputs (I/Os) to move data in and out complete the AI platform. These platforms need to be robust and may provide some safety guarantee, especially in the automotive space. Most of the established processor companies, as well as FPGA companies and cloud computing companies, are working on these types of architectures and platforms in order to accelerate their computations.
Accelerating AI holds enormous promise. More than 80 startups are working on AI accelerators, marvels Dr. Brinkmann, and this is an interesting and large space to be involved in right now. In the automotive space, engineers are considering centralized computerized platforms with high memory bandwidth and high-speed interconnect within the system to allow for more flexibility and lower cost overhead.
