Making AI Run Faster


The semiconductor industry has woken up to the fact that heterogeneous computing is the way forward and that inferencing will require more than a GPU or a CPU. The numbers being bandied about by the 30 or so companies working on this problem are 100X improvements in performance. But how to get there isn't so simple. It requires four major changes, as well as some other architectural shifts. ... » read more

Betting Big On Discontinuity


Wally Rhines, president and CEO of Mentor, a Siemens Business, sat down with Semiconductor Engineering to talk about the booming chip industry, what's driving it, how long it will last and what changes are ahead in EDA and chip architectures. What follows are excerpts of that conversation. SE: The EDA and semiconductor industries are doing well right now. What's driving that growth? Rhine... » read more

Intel’s Next Move


Gadi Singer, vice president and general manager of Intel's Artificial Intelligence Products Group, sat down with Semiconductor Engineering to talk about Intel's vision for deep learning and why the company is looking well beyond the x86 architecture and one-chip solutions. SE: What's changing on the processor side? Singer: The biggest change is the addition of deep learning and neural ne... » read more

Where ML Works Best


Anirudh Devgan, president of Cadence, sat down with Semiconductor Engineering to discuss machine learning inside and outside of EDA tools and how that will affect the future of chip and system design. What follows are excerpts of that discussion. SE: How do you see the market and use of machine learning shaping up? Devgan: There are three main areas—machine learning inside, machine lear... » read more

Right-Sizing Your Cryptographic Processing Solution


The cornerstone of all security solutions that deal with confidentiality, integrity and authentication is cryptography. Cryptography is a complex math problem used to help create security applications. Algorithms vary for different applications and are used for specific purposes. The common cryptographic algorithms are symmetric block ciphers for confidentiality, hash functions for integrity, a... » read more

Power/Performance Bits: July 10


Heating up EV batteries Researchers from Pennsylvania State University developed a self-heating battery that can charge rapidly in cold conditions, a step they hope could spread adoption of electric vehicles. "Electric vehicles are popular on the west coast because the weather is conducive," said Xiao-Guang Yang, assistant research professor in mechanical engineering, Penn State. "Once you ... » read more

Machine Learning’s Limits (Part 1)


Semiconductor Engineering sat down with Rob Aitken, an Arm fellow; Raik Brinkmann, CEO of OneSpin Solutions; Patrick Soheili, vice president of business and corporate development at eSilicon; and Chris Rowen, CEO of Babblelabs. What follows are excerpts of that conversation. SE: Where are we with machine learning? What problems still have to be resolved? Aitken: We're in a state where thi... » read more

The Impact of AI On Autonomous Vehicles


Automotive systems designers initially used traditional embedded-vision algorithms in advanced driver assistance systems (ADAS). One of the key enablers of vehicle autonomy moving forward will be the application of artificial intelligence (AI) techniques, particularly those based upon deep-learning algorithms implemented on multi-layer convolutional neural networks (CNNs). These algorithms show... » read more

IIoT And Predictive Maintenance


It’s every production line manager’s nightmare—some machinery breaks down, stopping production on the factory floor. In a fab, if just one piece of semiconductor manufacturing equipment goes down and is out of service for hours, wafer fabrication can grind to a halt. Such shutdowns are expensive, especially if the plant is operating on a 24-hour schedule to meet demand. One selling poi... » read more

Finding And Fixing ML’s Flaws


OneSpin CEO Raik Brinkmann sat down with Semiconductor Engineering to discuss how to make machine learning more robust, predictable and consistent, and new ways to identify and fix problems that may crop up as these systems are deployed. What follows are excerpts of that conversation. SE: How do we make sure devices developed with machine learning behave as they're supposed to, and how do we... » read more

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