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By Amelia Dalton, EE Journal | Feat. Rob van Blommestein, Head of Marketing, OneSpin
In this week’s episode of Fish Fry, we are swimming in SoCs! Randy Fish (UltraSoC) joins us to discuss the deep waters of embedded analytics and AI platform debug. Ramsay Allen (Moortec) and I chat about the rising tide of advanced chip node designs and the benefits of in-chip monitoring IP. Finally, Rob van Blommestein (OneSpin) and sail through the choppy waters of IC verification.
By Brian Bailey, Semiconductor Engineering | Featuring Tom Anderson, Technical Marketing, OneSpin
The core concepts in hardware-software co-design are getting another look, nearly two decades after this approach was first introduced and failed to catch on.
By Ann Steffora Mutschler, Semiconductor Engineering | Feat. Tom Anderson, Technical Marketing, OneSpin
Semiconductor Engineering sat down to discuss partitioning with Raymond Nijssen, vice president of system engineering at Achronix; Andy Ladd, CEO at Baum; Dave Kelf, chief marketing officer at Breker; Rod Metcalfe, product management group director in the Digital & Signoff Group at Cadence; Mark Olen, product marketing group manager at Mentor, a Siemens Business; Tom Anderson, technical marketing consultant at OneSpin; and Drew Wingard, CTO at Sonics [Sonics was acquired by Facebook in March 2019]. What follows are excerpts of that discussion.
By Brian Bailey, Semiconductor Engineering | Feat. Dominik Strasser, VP Engineering, OneSpin
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.
By Brian Bailey, Semiconductor Engineering | Featuring David Landoll, Solutions Architect, OneSpin
Experts at the Table: Who is responsible for safety and security and what can we do as an industry to make it better?
Semiconductor Engineering sat down to discuss industry attitudes towards safety and security with Dave Kelf, chief marketing officer for Breker Verification; Jacob Wiltgen, solutions architect for functional safety at Mentor, a Siemens Business; David Landoll, solutions architect for OneSpin Solutions; Dennis Ciplickas, vice president of characterization solutions at PDF Solutions; Andrew Dauman, vice president of engineering for Tortuga Logic; and Mike Bartley, chief executive officer for TV&S. This is the third part of this discussion.
[...]
Landoll: I hear that in DO-254 all the time. There is a push and pull that a lot of people doing implementations know that the energy being spent is not energy to make it safer, it is energy to get the compliance signed off. If I could put the energy into doing something else, I could actually make it safer. But I am not allowed to do that because it won’t be approved.
By Ann Steffora Mutschler, Semiconductor Engineering | Featuring Raik Brinkmann, President and CEO, OneSpin
Systems are extremely specific and power-constrained, which makes design extremely complex.
Adding intelligence to the edge is a lot more difficult than it might first appear, because it requires an understanding of what gets processed where based on assumptions about what the edge actually will look like over time.
[...]
“When you build systems, there are multiple things you need to care for,” said Raik Brinkman, CEO of OneSpin Solutions. “It’s the same whether you do it in hardware or software, but the challenge is how you keep track of data. Nothing is fixed, and as you get new data, you may find you have gaps and have to retrain systems. There are multiple layers of data. And with machine learning, you need to recompute everything. This is a big management task. People are not aware of the complexity in all of this. They’re happy enough that it works.”
Tesla’s autopilot chip executes 72-trillion additions and multiplications per second: It better get the math right...
ARTIFICIAL INTELLIGENCE (AI) is steadily progressing toward advanced, high-value applications that will have a profound impact on our society. Automobiles that can drive themselves are perhaps the most talked about, imminent technological revolution, but there are many more applications of AI.
AI software, such as a neural network (NN) implementing a machine learning (ML) or deep learning (DL) algorithm, requires high-performance “artificial brains,” or hardware, to run on. Computer vision is fundamental to many complex, safety-critical decision-making processes.
