The Evolution Of Deep Learning For ADAS Applications


Embedded vision solutions will be a key enabler for making automobiles fully autonomous. Giving an automobile a set of eyes – in the form of multiple cameras and image sensors – is a first step, but it also will be critical for the automobile to interpret content from those images and react accordingly. To accomplish this, embedded vision processors must be hardware optimized for performanc... » read more

Verification And The IoT


Semiconductor Engineering sat down to discuss what impact the IoT will have on the design cycle, with Christopher Lawless, director of external customer acceleration in [getentity id="22846" e_name="Intel"]'s Software Services Group; David Lacey, design and verification technologist at Hewlett Packard Enterprise; Jim Hogan, managing partner at Vista Ventures; Frank Schirrmeister, senior group d... » 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

An Easier Path To Faster C With FPGAs


For most scientists, what is inside a high-performance computing platform is a mystery. All they usually want to know is that a platform will run an advanced algorithm thrown at it. What happens when a subject matter expert creates a powerful model for an algorithm that in turn automatically generates C code that runs too slowly? FPGA experts have created an answer. More and more, the genera... » read more

What’s Missing From Machine Learning


Machine learning is everywhere. It's being used to optimize complex chips, balance power and performance inside of data centers, program robots, and to keep expensive electronics updated and operating. What's less obvious, though, is there are no commercially available tools to validate, verify and debug these systems once machines evolve beyond the final specification. The expectation is th... » read more