I wrote a while back about some of the more exotic architectures for machine learning (ML), especially for neural net (NN) training in the data center but also in some edge applications. In less hairy applications, we’re used to seeing CPU-based NNs at the low end, GPUs most commonly (and most widely known) in data centers as the workhorse… Read More
Artificial Intelligence
Achronix Assists Academics
In every semiconductor related field, innovation is the name of the game. Academic, non-profit and government research has been a consistent source of innovation. Look back at the US space program, basic science research and even military programs to see where much of the foundation of our current technological age came from.… Read More
Making AI Silicon Smart with PVT Monitoring
PVT – depending on what field you are in those three letters may mean totally different things. In my undergraduate field of study, chemistry, PVT meant Pressure, Volume & Temperature. Many of you probably remember PV=nRT, the dreaded ideal gas law. However, anybody working in semiconductors knows that PVT stands … Read More
Eta Compute Receives Two Awards from ARM at TechCon
Many startups set out with the goal of accomplishing a technical feat that was previously considered impossible. Quite frankly most do not succeed. Yet, occasionally a company comes along that succeeds with a game changing breakthrough. ETA Compute has done just this. Yet, even more impressively, this 3-year-old company has… Read More
NXP Strengthens Security, Broadens ML Application at the Edge
Security and machine learning (ML) are among the hottest areas in tech, especially for the IoT. The need for higher security is, or should be, blindingly obvious at this point. We struggle to fend off daily attacks even in our mainstream compute and networking environment. How defenseless will we be when we have billions of devices… Read More
Architecture for Machine Learning Applications at the Edge
Machine learning applications in data centers (or “the cloud”) have pervasively changed our environment. Advances in speech recognition and natural language understanding have enabled personal assistants to augment our daily lifestyle. Image classification and object recognition techniques enrich our social media experience,… Read More
The Cloud-Edge Debate Replays Inside the Car
I think we’re all familiar with the cloud/edge debate on where intelligence should sit. In the beginning the edge devices were going to be dumb nodes with just enough smarts to ship all their data to the cloud where the real magic would happen – recognizing objects, trends, need for repair, etc. Then we realized that wasn’t the best… Read More
Does the G in GDDR6 stand for Goldilocks?
In the wake of TSMC’s recent Open Innovation Platform event, I spoke to Frank Ferro, Senior Director of Product Management at Rambus. His presentation on advanced memory interfaces for high-performance systems helped to shed some light on the evolution of system memory for leading edge applications. System implementers now… Read More
Technology Behind the Chip
Tom Dillinger and I attended the Silvaco SURGE 2018 event in Silicon Valley last week with several hundred of our semiconductor brethren. Tom has a couple blogs ready to go but first let’s talk about the keynote by Silvaco CEO David Dutton. David isn’t your average EDA CEO, he spent the first 8 years of his career at Intel then spent … Read More
Highly Modular, AI Specialized, DNA 100 IP Core Target IoT to ADAS
The Cadence Tensilica DNA100 DSP IP core is not a one-size-fits-all device. But it’s highly modular in order to support AI processing at the edge, delivering from 0.5 TMAC for on-device IoT up to 10s or 100 TMACs to support autonomous vehicle (ADAS). If you remember the first talks about IoT and Cloud, a couple of years ago, the IoT … Read More
Flynn Was Right: How a 2003 Warning Foretold Today’s Architectural Pivot