Architecting Hardware Protection For Data At Rest And In Motion


Planning the security architecture for any device begins with the threat model. The threat model describes the types of attacks that the device or application may face and needs to be protected against. It is based on what attackers can do, what level of control they have over the product (i.e., remote or direct access), and how much effort and money they are willing and able to spend on an att... » read more

On-Chip FPGA: The “Other” Compute Resource


When system companies discuss processing requirements for their next generation products, the typical discussion invariably leads to: what should the processor subsystem look like? Do you upgrade the embedded processors in the current subsystem to the latest and greatest embedded CPU? Do you add more CPUs? Or perhaps add a little diversity by adding a DSP or GPU? One compute resource tha... » read more

Securing Connected And Autonomous Vehicles


Vehicles are on track to become highly sophisticated Internet of Things (IoT) devices. With the added functionality that connects vehicles to other vehicles, the infrastructure, and even pedestrians, the opportunity for hacking expands. Challenges like complexity and the burden of legacy systems further complicate the situation. The future of connected and autonomous vehicles (CAV) demands leve... » read more

Innovative Technology Drives Rapid Deployment Of New 5G Products, Services, And Business Models


The wireless future is about developing the most compelling products using a combination of advanced technologies to maximize system performance, while optimizing both cost and power. Doing so will unlock deployment of new 5G products and services for mobile operators and the whole 5G ecosystem, from businesses to consumers to the economy. With 5G offering so much potential, how can the industr... » read more

Meeting Processor Performance And Safety Requirements For New ADAS & Autonomous Vehicle Systems


By Fergus Casey and Srini Krishnaswami Innovation in today’s automotive industry is accelerating as companies race to be the market leader in safety and autonomous vehicles. With vehicle control moving from humans to the vehicles’ active safety systems, more sensors – cameras, radar, lidar, etc. – are being added to automotive systems. More sensors require more computational performa... » read more

Three Key Aspects Of IP Quality


It’s no secret that today’s huge system-on-chip (SoC) projects require massive amounts of design reuse. No team, no matter how talented, can design a billion or more gates from scratch. They use extensive borrowing of RTL code from previous and related projects, plus hundreds of thousands of instantiated IP blocks from internal libraries, open-source repositories, development partners, and ... » read more

More Than Moore At iMAPS


San Diego recently hosted the 54th International Symposium on Microelectronics. That's a very generic title, so you should know that it is run by iMAPS, the International Microelectronics Assembly and Packaging Society. Generally, the conference is just known as iMAPS. One of the keynotes was given by Cadence's KT Moore (in person). His presentation was titled "More Moore or More than Moore: a... » read more

Chip Design Teams And Restaurant Kitchen Staff Have A Lot In Common


By Anagha Pandharpurkar Believe it or not, electronic device and systems-design teams have a lot in common with kitchen staff in big commercial restaurants: They both leverage many different tools and resources to churn out great products in a high-pressure environment to a demanding audience that wants it now, not tomorrow. Unfortunately, design teams are often not nearly as well equippe... » read more

Solving Real World AI Productization Challenges With Adaptive Computing


The field of artificial intelligence (AI) moves swiftly, with the pace of innovation only accelerating. While the software industry has been successful in deploying AI in production, the hardware industry – including automotive, industrial, and smart retail – is still in its infancy in terms of AI productization. Major gaps still exist that hinder AI algorithm proof-of-concepts (PoC) from b... » read more

Getting Better Edge Performance & Efficiency From Acceleration-Aware ML Model Design


The advent of machine learning techniques has benefited greatly from the use of acceleration technology such as GPUs, TPUs and FPGAs. Indeed, without the use of acceleration technology, it’s likely that machine learning would have remained in the province of academia and not had the impact that it is having in our world today. Clearly, machine learning has become an important tool for solving... » read more

← Older posts Newer posts →