New Deep Learning Processors, Embedded FPGA Technologies, SoC Design Solutions


Some of the most valuable events at DAC are the IP Track sessions, which give small and midsize companies a chance to share innovations that might not get much attention elsewhere. The use of IP in SoCs has exploded in recent years. In a panel at DAC 2017, an industry expert noted that the IP market clearly was growing even faster than EDA itself, due to the fact that more and more chip mak... » read more

Deep Learning Neural Networks Drive Demands On Memory Bandwidth


A deep neural network (DNN) is a system that is designed similar to our current understanding of biological neural networks in the brain. DNNs are finding use in many applications, advancing at a fast pace, pushing the limits of existing silicon, and impacting the design of new computing architectures. Figure 1 shows a very basic form of neural network that has several nodes in each layer that ... » read more

Developing ASIL Ready SoCs For Self-Driving Cars


Artificial intelligence (AI) and deep learning using neural networks is a powerful technique for enabling advanced driver-assistance systems (ADAS) and greater autonomy in vehicles. As AI research moves rapidly, designers are facing tough competition to provide efficient, flexible, and scalable silicon and software to handle deep learning automotive applications like inferencing in embedded vis... » read more

System Bits: May 8


Unlocking the brain Stanford University researchers recently reminded that for years, the people developing artificial intelligence drew inspiration from what was known about the human brain, and now AI is starting to return the favor: while not explicitly designed to do so, certain AI systems seem to mimic our brains’ inner workings more closely than previously thought. [caption id="attach... » read more

Rules Of The Driverless Road


The growing disparity among states, countries and carmakers over autonomous driving is turning what should be a logical progression into chaos. Consider what's happening in California, which is determined to remain the leader in this tech revolution. The state last month relaxed its testing rules so that cars can be monitored remotely, with no driver actually present inside the car. I... » read more

Challenges At The Edge


By Kevin Fogarty and Ed Sperling Edge computing is inching toward the mainstream as the tech industry begins grappling with the fact that far too much data will be generated by sensors to send everything back to the cloud for processing. The initial idea behind the IoT/IIoT, as well as other connected devices, was that simple sensors would relay raw data to the cloud for processing throug... » read more

The Great Chip Shakeup


Facebook, Alibaba, Google, Apple and Samsung are all designing their own chips. So are Cisco and Huawei. So what exactly does this mean for big chipmakers and the semiconductor ecosystem? While your first impulse might be to draw a straight line between Qualcomm's decision to cut 1,500 jobs and reports about giant systems companies developing chips in-house, it's not clear there is any corre... » read more

Neural Nets In ADAS And Autonomous Driving SoC Designs


Automotive electronics has ushered in a new wave of semiconductor design innovation and one new technology gaining a lot of attention is neural networks (NNs). Advanced driving assistance systems (ADAS) and autonomous car designs now rely on NNs to meet the real-time requirements of complex object-recognition algorithms. The concept of NNs has been around since World War II, promising a futu... » read more

Deep Learning And The Future


Following up from my last post on our deep learning event at the Computer History Museum – “ASICs Unlock Deep Learning Innovation,” I’d like to take a glimpse into the future. Like many such discussions, it’s often useful to take a look back first to try and make sense out of what is to come.  That’s essentlially what our keynote speaker, Ty Garibay, did at the event. Ty is the CTO... » read more

System Bits: April 17


Smartphone microscopes transformed into lab-grade devices with deep learning UCLA Samueli School of Engineering researchers have demonstrated that deep learning techniques can discern and enhance microscopic details in photos taken by smartphones in order to improve the resolution and color details of smartphone images so much that they approach the quality of images from laboratory-grade mic... » read more

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