AI’s Power To Transform Semiconductor Design And Manufacturing


Artificial intelligence and machine learning (AI/ML) have immense power to transform semiconductor design and manufacturing for a variety of broad and far-ranging applications. Just consider the volume of data generated by design and manufacturing each year. With increasingly complex products, machines, processes and supply chains, the overall amount of data associated with semiconductor making... » read more

Big Changes In Optical Inspection


Optical inspection always has been the workhorse technology for finding defects in chips. It's fast, cost-efficient, and generally reliable enough for most chips. But as logic scales into the angstrom range, and as systems become collections of chiplets, optical inspection needs to be combined with other types of inspection such as X-ray and acoustic. Kyle Vander Schaaf, application engineer at... » read more

The Long Climb: Bringing Through Glass Vias (TGV) To High-Volume Manufacturing


The semiconductor industry is a land of peaks and valleys. It’s a place where each innovation represents the culmination of a long and often difficult climb to the summit. In the case of glass substrates, the peak of the mountain is in sight. The arrival of glass substrates comes at an opportune time, as the industry eyes new process innovations to meet the incredible demand for high perfo... » read more

Advancements In Silicon Device Technology And Design Driving New SLM Monitor Categories


Silicon, the foundation of modern electronics, has seen continuous advancements since the early days of integrated circuits. The pace of innovation has been driven by the relentless quest for miniaturization, increased performance, and efficiency. However, Moore’s Law is no longer a given and silicon is facing functional limitations as technology scales. To address these challenges and conti... » read more

Metrology Advances Step Up To Sub-2nm Device Node Needs


Metrology and inspection are dealing with a slew of issues tied to 3D measurements, buried defects, and higher sensitivity as device features continue to shrink to 2nm and below. This is made even more challenging due to increasing pressure to ramp new processes more quickly. Metrology tool suppliers must exceed current needs by a process node or two to ensure solutions are ready to meet tig... » read more

From Reaction To Prevention In Data Center RAS


The rise of artificial intelligence (AI), cloud services, and IoT has fueled the rapid expansion of hyperscale data centers. These massive facilities house thousands of servers, all working to support an increasingly digital world. But as the scale of data centers grows, so too does the need for reliable and high-performance semiconductors. Semiconductor failures and inconsistencies can cause s... » read more

Complex Heterogeneous Integration Drives Innovation In Semiconductor Test


Heterogeneous integration is driving innovation in the semiconductor industry, but it also introduces more complexity in chip design, which translates to more intricate test requirements. The automated test equipment (ATE) industry is responding, developing and utilizing more sophisticated test equipment capable of handling the diverse functionalities and interfaces needed to test heterogeneous... » read more

New Challenges In IC Reliability


Experts at the Table: Semiconductor Engineering sat down to discuss reliability of chips, how it is changing, and where the new challenges are, with Steve Pateras, vice president of marketing and business development at Synopsys; Noam Brousard, vice president of solutions engineering at proteanTecs; Harry Foster, chief verification scientist at Siemens EDA; and Jerome Toublanc, high-tech soluti... » read more

Redefining RAS in Datacenters with Real-Time Health Monitoring


Abstract Hyperscale datacenters require intense computational power for compute-intensive tasks, such as AI, data analytics, machine learning, and big data processing. They leverage parallel processing across multiple computers, in high-density servers, to handle complex tasks efficiently. This uses specialized, powerful processors and training and inference of specific GPUs or ASICs. Such c... » read more

ML Model Usage For Various Life Stages Of Semiconductor Test


By Shinji Hioki and Ken Butler From development through high volume manufacturing (HVM), semiconductor manufacturers’ pain points change based on the life stages. Each stage requires different types of applications to help with business needs. At the early stage, where the design and process are still immature, understanding the root causes of maverick material and implementing fixes is th... » read more

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