This is another installment covering TSMC’s very popular Open Innovation Platform event (OIP), held on August 25. This event presents a diverse and high-impact series of presentations describing how TSMC’s vast ecosystem collaborates with each other and with TSMC. The presentation covered here from Synopsys focuses on the… Read More
Artificial Intelligence (AI) and Machine Learning (ML) are becoming more and more commonplace in our world. We have Siri, Alexa and Google Assistant that understand our voice commands. Vision systems that recognize objects are used for facial recognition, autonomous driving, medical, geographical and many other applications.… Read More
For a long time, memories were the primary technology driver for process development. If you built memories, you got access to cutting-edge process information. If you built other products, this could give you a competitive edge. In many cases, FPGAs are replacing memories as the driver for advanced processes. The technology… Read More
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
The basic principles used for neural networks have been understood for decades, what have changed to make them so successful in recent years are increased processing power, storage and training data. Layered on top of this is continued improvement in algorithms, often enabled by dramatic hardware performance improvements.… 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
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
Deep learning (DL) has become the oracle of our age – the universal technology we turn to for answers to almost any hard problem. This is not surprising; its strength in image and speech recognition, language processing and multiple other domains amaze and shock us, to the point that we’re now debating AI singularities. But then,… Read More
Cadence has recently announced two key design-in for their Vision DSP IP family: MediaTek’s Helio P30 integrates the Tensilica Vision P5 DSP and HiSilicon has selected the Cadence® Tensilica® Vision P6 DSP for its 10nm Kirin 970 mobile application processor. The Kirin 970 being integrated into Huawei’s new Mate 10 Series mobile… Read More
Before the advent of convolutional neural networks (CNN), image processing was done with algorithms like HOG, SIFT and SURF. This kind of work was frequently done in data centers and server farms. To facilitate mobile and embedded processing a new class of processors was developed – the vision processor. In addition to doing a … Read More
