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Artificial Intelligence
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
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
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
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
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
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
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
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
I commented recently on limitations in deep learning (DL), one of which is the inability to incorporate prior knowledge, like basic laws of mathematics or physics. Typically, understanding in DL must be inferred from the training set, which in a general sense cannot practically cover prior knowledge. Indeed one of the selling… Read More
AI is revolutionizing and transforming virtually every industry in the digital world. Advances in computing power and deep learning have enabled AI to reach a tipping point toward major disruption and rapid advancement. However, these applications require much higher performance and bandwidth requiring new kinds of IP and… Read More
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