Applying Machine Learning


Sundari Mitra, co-founder and CEO of NetSpeed Systems, sat down with Semiconductor Engineering to discuss machine learning, training algorithms, what customers are struggling with today, and how startups fare in an increasingly consolidated semiconductor industry. What follows are excerpts of that conversation. SE: Machine learning is booming. How will this change design? Mitra: This is a... » read more

Using CNNs To Speed Up Systems


Convolutional neural networks (CNNs) are becoming one of the key differentiators in system performance, reversing a decades-old trend that equated speed with processor clock frequencies, the number of transistors, and the instruction set architecture. Even with today's smartphones and PCs, it's difficult for users to differentiate between processors with 6, 8 or 16 cores. But as the amount o... » read more

Speeding Up Neural Networks


Neural networking is gaining traction as the best way of collecting and moving critical data from the physical world and processing it in the digital world. Now the question is how to speed up this whole process. But it isn't a straightforward engineering challenge. Neural networking itself is in a state of almost constant flux and development, which makes it something of a moving target. Th... » read more

The Efficiency Problem


The field of automotive automation has been the driver – so to speak – of the next leap of innovation in the field of transportation. Car architectures are being re-engineered to take advantage of incredible leaps in automation, using more powerful processors that process more data than ever before. The recent focus on autonomous automobile technology could be due to the ongoing drop in ... » read more

Supporting CPUs Plus FPGAs


While it has been possible to pair a CPU and FPGA for quite some time, two things have changed recently. First, the industry has reduced the latency of the connection between them and second, we now appear to have the killer app for this combination. Semiconductor Engineering sat down to discuss these changes and the state of the tool chain to support this combination, with Kent Orthner, system... » read more

What Does An AI Chip Look Like?


Depending upon your point of reference, artificial intelligence will be the next big thing or it will play a major role in all of the next big things. This explains the frenzy of activity in this sector over the past 18 months. Big companies are paying billions of dollars to acquire startup companies, and even more for R&D. In addition, governments around the globe are pouring additional... » read more

System Bits: June 28


Deep-learning-based virtual reality tool Given that future systems which enable people to interact with virtual environments will require computers to interpret the human hand’s nearly endless variety and complexity of changing motions and joint angles, Purdue University researchers have created a convolutional neural network-based system that is capable of deep learning. [caption id="att... » read more

Convolutional Neural Networks Power Ahead


While the term may not be immediately recognizable, convolutional neural networks (CNNs) are already part of our daily lives—and they are expected to become even more significant in the near future. [getkc id="261" kc_name="Convolutional neural networks"] are a form of machine learning modeled on the way the brain's visual cortex distinguishes one object from another. That helps explain wh... » read more

What Cognitive Computing Means For Chip Design


Cognitive computing. Artificial intelligence. Machine learning. All of these are concepts aim to make human types of problems computable, whether it be a self-driving car, a health care-providing robot, or a walking and talking assistant robot for the home or office. R&D teams around the world are working to create a whole new world of machines more intelligent than humans. Designing sys... » read more

Integration Or Segregation


In the Electronics Butterfly Effect story, the observation was made that the electronics industry has gone non-linear, no longer supported by incremental density and cost-reducing improvements that Moore’s Law promised with each new node. Those incremental changes, over several decades, have meant that design and architecture have followed a predictable path with very few new ideas coming in ... » read more

← Older posts