Author's Latest Posts


Challenges In Stacking HBM


AI data centers are pushing for higher density in high-bandwidth memory. Today, the maximum number of layers that can be stacked is 8, but that increases to as many as 24 layers by 2030. The big challenge will be in the interconnects, and making sure the microbumps align. At 16 layers, the bump pitch will be less than 10 microns, and the dies will be thinner. Damon Tsai, head of product marketi... » read more

AI’s Value In Chip Design Depends On Data Availability


Experts at the Table: Semiconductor Engineering sat down to discuss the advantages and challenges in using AI in designing chips, with Chuck Alpert, Cadence Fellow; Sathish Balasubramanian, head of product marketing and senior director for custom IC at Siemens EDA; Anand Thiruvengadam, senior director and head of AI product management at Synopsys; Sailesh Kumar, CEO of Baya Systems; Mehir ... » read more

Preparing For The Quantum Computing Age


Within a decade, quantum computers will be able to break virtually any encryption algorithm in use today. What used to be science fiction is on its way to becoming a commercial reality. Once that happens, quantum computers will be able to crack in minutes what was supposed to be unbreakable for more than a century using the most powerful computers available. Erik Wood, senior director of crypto... » read more

Advanced Part Average Testing For Chips


Part average testing, one of the mainstays of semiconductor test, is becoming much more challenging at advanced nodes and in multi-die assemblies. In the past, PAT produced a Gaussian distribution that made it relatively simple to find outliers. That's no longer the case. Advanced packaging and leading-edge designs have unique attributes that determine which rules apply, such as the thickness o... » read more

Machine Learning In Semiconductor Manufacturing


Second in a seven-part series: Machine learning is a mathematical construct that is the foundation for nearly all the advancements in AI. ML came first, but it remains relevant even today. It can be applied to semiconductor fab for such things as predictive maintenance of manufacturing equipment, rather than just maintenance on a schedule, which decreases downtime. But getting this right is har... » read more

Best Options For Using AI In Chip Design


Experts at the Table: Semiconductor Engineering sat down to discuss how and where AI can be applied to chip design to maximize its value, and how that will impact the design process, with Chuck Alpert, Cadence Fellow; Sathish Balasubramanian, head of product marketing and senior director for custom IC at Siemens EDA; Anand Thiruvengadam, senior director and head of AI product management at S... » read more

AI, From A To Z


First in a seven-part series: What's the difference between AI, ML, DL, LLMs, and agentic AI? Is it truly revolutionary, or is it an evolutionary series of steps that have enabled machines to do much more than in the past? Jon Herlocker, vice president and general manager of software analytics at Cohu, talks about the evolution of AI over nearly 70 years, the chain of innovation that has enable... » read more

Workload-Specific Hardware Accelerators


Workload-specific hardware accelerators are becoming essential in large data centers for two reasons. One is that general-purpose processing elements cannot keep up with the workload demands or latency requirements. The second is that they need to be extremely efficient due to limited electricity from the grid and the high cost of cooling these devices. Sharad Chole, chief scientist and co-foun... » read more

What’s Different About HBM4


Memory bandwidth is limiting the flow of huge datasets that are needed to train AI models. There is much more data to process, store, and retrieve, but the speed at which that data moves through high-bandwidth memory (HBM) stacks is significantly lower than the speed at which data can be processed. Frank Ferro, group director for product management at Cadence, talks about the new HBM4 standard,... » read more

Agentic AI: Lots Of Little Black Boxes


AI is changing so quickly that it's not always clear how much of a security threat it poses for semiconductor design, and that uncertainty increases as AI agents are introduced into the mix. So far, the use of AI in chip design has been highly targeted. Most of what is included in design tools is some version of machine learning, bounded by tight control loops. EDA and IP vendors, large chip... » read more

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