More Semiconductor Data Moving To Cloud


The cloud is booming. After years of steady growth it has begun to spike, creating new options for design, test, analytics and AI, all of which have an impact on every segment of the semiconductor industry. The initial idea behind the cloud is that it would supplement processing done on premises, adding extra processing power wherever necessary, such as in the verification and debug stages o... » read more

How Many Test Miles Make A Vehicle Safe?


The road to reliable safety testing of autonomous vehicles (AVs) is shifting left. Standards groups are beginning to publish functional safety standards that could make it possible to verify what a machine-learning AV pilot application will do in a traffic situation even before hardware or software is released from validation testing. This kind of approach has been possible for some time in ... » read more

AI/ML’s Role In ADAS


Self-driving cars are headed this way, but not for a while. And that’s not a bad thing. As I discuss in my article, “Where Should Auto Sensor Data Be Processed?” there is still much to be worked out just on the technology side, such as how and where to process the significant amount of data coming into the vehicle from the outside world. [caption id="attachment_24152605" align="al... » read more

Security’s Very Strange Path To Success


Security at the chip level appears to be heading toward a more promising future. The reason is simple—more people are willing to pay for security than in the past. For the most part, security is like insurance. You don't know it's working until something goes wrong, and you don't necessarily even know right away if there has been a breach. Sometimes it takes years to show up, because it ca... » read more

Using Synopsys Z01X To Accelerate The Fault Injection Campaign Of A Fully Configurable IP


By Arteris IP Alexis Boutillier, Corporate Application Manager, Safety Manager, and Mohan Krishnareddy, Solution Engineer, at the Synopsys Users Group (SNUG), March 2018, Santa Clara, CA. Principles and real-world practices of ISO 26262 for semiconductor design teams. After providing an overview of how functional safety affects management, development, and supporting processes, the paper exp... » read more

Adding Order And Structure To Verification


You can't improve what you can't measure, and when it comes to methodologies the notion of measurement becomes more difficult. Add in notions of the skills, capabilities and experience levels of individuals within an organization, which may affect their ability to adopt certain technologies, and it requires considerable attention. This is where concepts such as capability maturity models (CM... » read more

Big Shift In Multi-Core Design


Hardware and software engineers have a long history of working independently of each other, but that insular behavior is changing in emerging areas such as AI, machine learning and automotive as the emphasis shifts to the system level. As these new markets consume more semiconductor content, they are having a big impact on the overall design process. The starting point in many of these desig... » read more

Fundamentals of Semiconductor ISO 26262 Certification: People, Process and Product


Written by Kurt Shuler, VP of Marketing at Arteris IP Developers of automotive semiconductor devices and electronic systems beware: There may be some vendors who claim their products meet the ISO 26262 safety standard requirements for integration into the production of passenger vehicles without fully understanding the nature of the challenge. These claims might be superficial if they fail... » read more

AI Training Chips


Kurt Shuler, vice president of marketing at Arteris IP, talks with Semiconductor Engineering about how to architect an AI training chip, how different processing elements are used to accelerate training algorithms, and how to achieve improved performance. https://youtu.be/4cnBCX-9jlk     See other tech talk videos here. » read more

What Makes A Good AI Accelerator


The rapid growth and dynamic nature of AI and machine learning algorithms is sparking a rush to develop accelerators that can be optimized for different types of data. Where one general-purpose processor was considered sufficient in the past, there are now dozens vying for a slice of the market. As with any optimized system, architecting an accelerator — which is now the main processing en... » read more

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