Silicon Carbide’s Superpowers


As we enter a new computing era driven by the Internet of Things (IoT), Big Data and Artificial Intelligence (AI), demand is growing for more energy-efficient chips. In this context, we usually think about Moore’s Law and reducing the size of transistors. However, advances in power semiconductors are not governed by node size reduction. Silicon power switches, such as MOSFETs and IGBTs, ar... » read more

Process Control For Next-Generation Memories


The Internet of Things (IoT), Big Data and Artificial Intelligence (AI) are driving the need for higher speeds and more power-efficient computing. The industry is responding by bringing new memory technologies to the marketplace. Three new types of memory in particular—MRAM (magnetic random access memory), PCRAM (phase change RAM) and ReRAM (resistive RAM)—are emerging as leading candidat... » read more

New Applications Call For New Memory Types


The semiconductor industry is on the verge of a transformative computing era driven by Big Data, Artificial Intelligence (AI) and the Internet of Things (IoT). However, achieving the improvements in computing performance and efficiency needed for new AI and IoT applications represent some of the biggest technology challenges the industry has faced. Among the most critical requirements is del... » read more

New Imaging Tech Finds Buried Defects


By Shinsuke Mizuno and Vadim Kuchik Defects and contamination on the wafer can slow process development times and limit performance and yield. As chips get more complex, more defects can become buried within the increasing number of layers in the design. Finding and analyzing these buried defects is a major challenge for the industry, especially during the early learning cycles of new manufa... » read more

Comparing New Memory Types


After decades of research and development, three new types of memory—magnetic RAM (MRAM), phase change memory (PCRAM) and resistive RAM (ReRAM)—are moving toward commercial adoption, making this an exciting time for the semiconductor and computing industries. All three of these emerging memories are enabled by new materials and will require breakthroughs in process technology and manufactur... » read more

Selective Removal For Stronger Fins


By Matt Cogorno and Toshihiko Miyashita Remember when we could charge our mobile phones on a Sunday and not even think about it again until the next weekend? There was a time when battery life wasn’t even in the top ten concerns when purchasing a mobile phone. Today however, smartphones are constantly being used for computing, gaming, video streaming and other power-hungry applications, so... » read more

Multiple Approaches To Memory Challenges


As we enter the era of Big Data and Artificial Intelligence (AI), it is amazing to think about the possibilities for a truly seismic shift in the changing requirements for memory solutions. The massive amount of data humans generate every year is astounding and yet is expected to increase five-fold in the next few years from machine-generated data. Further compounding this growth is the emergin... » read more

Keeping Up Power And Performance With Cobalt


Chip designers require simultaneous improvements in “PPAC”: power, performance and area/cost (Fig. 1). Achieving these improvements is becoming increasingly difficult as classic Moore's Law scaling slows. What's needed is a new playbook for the industry consisting of new materials, new architectures, new 3D structures within the chip, new methods to shrink feature geometries, and advanced p... » read more

What’s Changing In Memory


As emerging big data and artificial intelligence (AI) applications, including machine learning, drive innovations across many industries, the issue of how to advance memory technologies to meet evolving computing requirements presents several challenges for the industry. The mainstream memory technologies, DRAM and NAND flash, have long been reliable industry workhorses, each optimized for s... » read more

A VC View Of The AI Landscape


In this blog post, I’ll highlight my takeaways from the recent AI Hardware Summit where I participated as a panelist. The conference’s focus on developing hardware accelerators for neural networks and computer vision attracted companies from across the ecosystem – AI chip startups, semiconductor companies, system vendors/OEMs, data center providers, financial services companies and VCs,... » read more

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