New Uses For Manufacturing Data


The semiconductor industry is becoming more reliant on data analytics to ensure that a chip will work as expected over its projected lifetime, but that data is frequently inconsistent or incomplete, and some of the most useful data is being hoarded by companies for competitive reasons. The volume of data is rising at each new process node, where there are simply more things to keep track of,... » read more

Who Owns A Car’s Chip Architecture


Kurt Shuler, vice president of marketing at Arteris IP, examines the competitive battle brewing between OEMs and Tier 1s over who owns the architecture of the electronic systems and the underlying chip hardware. This has become a growing point of contention as both struggle for differentiation in a market where increasingly autonomous vehicles will all behave the same way. That, in turn, has si... » read more

The Big Data Revolution Beautiful Servant Or Dangerous Monster?


The world is experiencing the revolution of information, humanity shifting the hegemony from science onto data. Just as the printing revolution once flooded the world with information, now cybernetic space is engulfing the entire planet with enormous amounts of information particles. We are living in an era where knowledgeability, facts, and big data have completely taken over, and control us a... » read more

Big Problems In A Little Data World


Lam Executive Vice President and Chief Technology Officer, Richard A. Gottscho, gave a keynote at the SEMI Industry Strategy Symposium (ISS), the annual executive conference for the semiconductor industry. Titled “I’m Living in a Little Data World, but I Have a Big Problem,” Rick talked about the challenges faced by the “little data world” of process development and the potential for ... » read more

3 Big Data Mega Trends For 2020


What are the greatest trends and challenges that will define the automotive and semiconductor industries in 2020? Our e-book delves deep into three of these megatrends: Artificial intelligence and machine learning at scale Holistic quality solutions Connected supply chains With automotive and semiconductor manufacturers under mounting pressure to manufacture products of the hig... » read more

AI And Big Data Set To Reinvent Semiconductor Industry


The recent IEEE International Electron Devices Meeting (IEDM) reaffirmed that the semiconductor industry is in a period of reinvention as we grapple with the challenges and opportunities promised by the Internet of Things (IoT), Big Data and AI. That such change is underway was made evident by a panel I was honored to moderate titled, “The Future of Logic: EUV is Here, Now What?” Joining... » read more

Making 3D Structures And Packages More Reliable


The move to smaller vertical structures and complex packaging schemes is straining existing testing approaches, particularly in heterogeneous combinations on a single chip and in multi-die packages. The complexity of these devices has exploded with the slowdown in scaling, as chipmakers turn to architectural solutions and new transistor structures rather than just relying on shrinking featur... » read more

The Evolution Of Pervasive Computing


The computing world has gone full circle toward pervasive computing. In fact, it has done so more than once, which from the outside may look like a more rapid spin cycle than a real change of direction. Dig deeper, though, and it's apparent that some fundamental changes are at work. This genesis of pervasive computing dates back to the introduction of the PC in 1981, prior to which all corpo... » read more

Verification In The Era Of Autonomous Driving, Artificial Intelligence And Machine Learning


The last couple of weeks have been busy with me participating on three panels that dealt with AI and machine learning in the contexts of automotive and aero/defense, in San Jose, Berlin and Detroit. The common theme? Data is indeed the new oil, and it messes with traditional value creation in electronics. Also, requirements for system design and verification are changing and there are completel... » read more

Compressing Datasets Created During Silicon Design


Authors: Guru Rao, Distinguished Engineer; Shakir Abbas, Software Engineering Group Director; Mohammad Mirfendereski, Configuration Management Architect; Cadence. Harsh Sharangpani, CEO and CTO; Rajesh Patil, VP-Business Development; Ascava. During the design cycle for modern semiconductor components, a very large amount of data is generated and stored, often accumulating to hundreds of tera... » read more

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