Big Shift In Multi-Core Design


Hardware and software engineers have a long history of working independently of each other, but that insular behavior is changing in emerging areas such as AI, machine learning and automotive as the emphasis shifts to the system level. As these new markets consume more semiconductor content, they are having a big impact on the overall design process. The starting point in many of these desig... » read more

Utilizing More Data To Improve Chip Design


Just about every step of the IC tool flow generates some amount of data. But certain steps generate a mind-boggling amount of data, not all of which is of equal value. The challenge is figuring out what's important for which parts of the design flow. That determines what to extract and loop back to engineers, and when that needs to be done in order to improve the reliability of increasingly com... » read more

The Automation Of AI


Semiconductor Engineering sat down to discuss the role that EDA has in automating artificial intelligence and machine learning with Doug Letcher, president and CEO of Metrics; Daniel Hansson, CEO of Verifyter; Harry Foster, chief scientist verification for Mentor, a Siemens Business; Larry Melling, product management director for Cadence; Manish Pandey, Synopsys fellow; and Raik Brinkmann, CEO ... » read more

Can Debug Be Tamed?


Debug consumes more time than any other aspect of the chip design and verification process, and it adds uncertainty and risk to semiconductor development because there are always lingering questions about whether enough bugs were caught in the allotted amount of time. Recent figures suggest that the problem is getting worse, too, as complexity and demand for reliability continue to rise. The... » read more

Pushing AI Into The Mainstream


Artificial intelligence is emerging as the driving force behind many advancements in technology, even though the industry has merely scratched the surface of what may be possible. But how deeply AI penetrates different market segments and technologies, and how quickly it pushes into the mainstream, depend on a variety of issues that still must be resolved. In addition to a plethora of techni... » read more

AI Chip Architectures Race To The Edge


As machine-learning apps start showing up in endpoint devices and along the network edge of the IoT, the accelerators that make AI possible may look more like FPGA and SoC modules than current data-center-bound chips from Intel or Nvidia. Artificial intelligence and machine learning need powerful chips for computing answers (inference) from large data sets (training). Most AI chips—both tr... » read more

Always-on Face Unlock


Accurate face verification has long been considered a challenge due to the number of variables, ranging from lighting to pose and facial expression. This white paper looks at a new approach—combining classic and modern machine learning (deep learning) techniques—that achieves 98.36% accuracy, running efficiently on Arm ML-optimized platforms, and addressing key security issues such as mu... » read more