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
Artificial Intelligence
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
Semiconductor IP Reality Check
A robust, proven library of IP is a critical enabler for the entire semiconductor ecosystem. Without it, ASIC design is pretty much impossible, given time-to-market pressures. Said another way, designing IP for your next chip simply doesn’t fit the schedule – most teams have barely enough time to integrate and validate pre-existing… Read More
DesignWare IP as AI Building Blocks
AI is disruptive and transformative to many status quos. Its manifestation can be increasingly seen in many business transactions and various aspects of our lives. While machine learning (ML) and deep learning (DL) have acted as its catalysts on the software side, GPU and now ML/DL accelerators are spawning across the hardware… Read More
The Robots are Coming!
Moshe Sheier, VP Marketing at CEVA, recently got back from MWC Shanghai and commented that robots are clearly trending. He saw hordes of robots from dozens of companies, begging for someone to brand and offer them in any one of many possible applications: in an airport to guide you to a connecting flight, for elder care, in hospitals… Read More
Computer Vision Design with HLS
I’m on a mini-roll on the subject of high-level design for ML-based systems. No complaints from me, this is one of my favorite domains and is certainly a hot area; it’s great to that EDA vendors are so active in advancing ML-based design. Here I want to talk about the Catapult HLS flow for use in ML design.
Since I’ve covered the ML topic… Read More
Webinar: NetSpeed is about to change the way SOCs are designed
A large part of the effort in designing SOCs has shifted to the integration of their constituent IP blocks. Many IP blocks used in SOCs come as ready to use components and the real work has become making them work together. Network on Chip (NoC) has been a huge help in this task, handling the interconnections between blocks and planning… Read More
Architecting an ML Design
Discussion on machine learning (ML) and hardware design has been picking up significantly in two fascinating areas: how ML can advance hardware design methods and how hardware design methods can advance building ML systems. Here I’ll talk about the latter, particularly about architecting ML-enabled SoCs. This approach is … Read More


The Foundry Model Is Morphing — Again