We started working with Felx Logix more than eight years ago and let me tell you it has been an interesting journey. Geoff Tate was our second CEO Interview so this is a follow up to that. The first one garnered more than 15,000 views and I expect more this time given the continued success of Flex Logix pioneering the eFPGA market, absolutely.… Read More
Tag: AI
Webinar: Real-time In-Chip Monitoring to Boost multi-core AI, ML, DL Systems
During the COVID-19 pandemic I’m using Zoom and attending more webinars to keep updated on semiconductor industry trends, and one huge trend is the importance of AI applied to SoCs. Using more cores to handle ML and DL makes sense, but then how do you keep the chips within their power and reliability limits while at the same … Read More
How does TensorFlow Lite on Tensilica HiFi DSP IP Sound?
In all the hubbub about AI/ML, it’s easy to see why visual ML gets more attention. It’s got appeal because of applications such as autonomous driving. Because of this it’s easy to overlook the importance of audio ML. I own a Tesla and putting it into autopilot is very cool, but even it has voice recognition built in as an important feature… Read More
There is No Easy Fix to AI Privacy Problems
Artificial intelligence – more specifically, the machine learning (ML) subset of AI – has a number of privacy problems.
Not only does ML require vast amounts of data for the training process, but the derived system is also provided with access to even greater volumes of data as part of the inference processing while in operation. … Read More
AI Interposer Power Modeling and HBM Power Noise Prediction Studies
I attended a session on 2.5D silicon interposer analysis at DesignCon 2020. Like many presentations at this show, ecosystem collaboration was a focus. In this session, Jinsong Hu (principal application engineer at Cadence) and Yongsong He (senior staff engineer at Enflame Tech) presented approaches for interposer power modeling… Read More
Specialized Accelerators Needed for Cloud Based ML Training
The use of machine learning (ML) to solve complex problems that could not previously be addressed by traditional computing is expanding at an accelerating rate. Even with advances in neural network design, ML’s efficiency and accuracy are highly dependent on the training process. The methods used for training evolved from CPU… Read More
FPGAs in the 5G Era!
FPGAs, today and throughout the history of semiconductors, play a critical role in design enablement and electronic systems. Which is why we included the history of FPGAs in our book “Fabless: The Transformation of the Semiconductor Industry” and added a new chapter in the 2019 edition on the history of Achronix.
In a recent blog… Read More
IEDM 2019 – Applied Materials panel EUV Recap
On Tuesday night of IEDM, Applied Materials held a panel discussion “The Future of Logic: EUV is Here, Now What?”. The panelists were: Regina Freed, managing director at Applied Materials as the moderator, Geoffrey Yeap, senior director of advanced technology at TSMC, Bala Haran, director of silicon process research at IBM, … Read More
Webinar – AI/ML SoC Memory and Interconnect IP Perspectives
For decades development work on Artificial Intelligence (AI) and Machine Learning (ML) was done on traditional CPUs and memory configurations. Now that we are in the “hockey stick” upturn in deployment of AI and ML, the search is on for the most efficient types of processing architectures. The result is a wave of development for… Read More
Synopsys and Infineon prepare for expanding AI use in automotive applications
We all know that cars are using processors for many tasks, but it is easy to fail to comprehend just how many there are in a typical modern car. Browsing through the Infineon AURIX automotive processor application guide, you can start to see just how pervasive processors are. The AURIX processors are specifically designed for automotive… Read More