Dramatic Changes Ahead For Chips And Systems


Early this year, most people had never heard of generative AI. Now the entire world is racing to capitalize on it, and that's just the beginning. New markets, such as spatial computing, quantum computing, 6G, smart infrastructure, sustainability, and many more are accelerating the need to process more data faster, more efficiently, and with much more domain specificity. Compared to the days ... » read more

2023: A Good Year For Semiconductors


Looking back, 2023 has had more than its fair share of surprises, but who were the winners and losers? The good news is that by the end of the year, almost everyone was happy. That is not how we exited 2022, where there was overcapacity, inventories had built up in many parts of the industry, and few sectors — apart from data centers — were seeing much growth. The supposed new leaders we... » read more

Fabs Begin Ramping Up Machine Learning


Fabs are beginning to deploy machine learning models to drill deep into complex processes, leveraging both vast compute power and significant advances in ML. All of this is necessary as dimensions shrink and complexity increases with new materials and structures, processes, and packaging options, and as demand for reliability increases. Building robust models requires training the algorithms... » read more

Proprietary Vs. Commercial Chiplets


Large chipmakers are focusing on chiplets as the best path forward for integrating more functions into electronic devices. The challenge now is how to pull the rest of the chip industry along, creating a marketplace for third-party chiplets that can be chosen from a menu using specific criteria that can speed time to market, help to control costs, and behave as reliably as chiplets developed in... » read more

Modeling Compute In Memory With Biological Efficiency


The growing popularity of generative AI, which uses natural language to help users make sense of unstructured data, is forcing sweeping changes in how compute resources are designed and deployed. In a panel discussion on artificial intelligence at last week’s IEEE Electron Device Meeting, IBM’s Nicole Saulnier described it as a major breakthrough that should allow AI tools to assist huma... » read more

Using Real Workloads To Assess Thermal Impacts


Thermal analysis is being driven much further left in the design, fueled by demand for increased transistor density and more features on a chip or in a package, as well as the unique ways the various components may be exercised or stressed. However, getting a clear picture of the thermal activity in advanced-node chips and packages is extremely complex, and it can vary significantly by use c... » read more

Data Formats For Inference On The Edge


AI/ML training traditionally has been performed using floating point data formats, primarily because that is what was available. But this usually isn't a viable option for inference on the edge, where more compact data formats are needed to reduce area and power. Compact data formats use less space, which is important in edge devices, but the bigger concern is the power needed to move around... » read more

Next-Gen Power Integrity Challenges


Experts at the Table: Semiconductor Engineering sat down to discuss power integrity challenges and best practices in designs at 7nm and below, and in 2.5D and 3D-IC packages, with Chip Stratakos, partner, physical design at Microsoft; Mohit Jain, principal engineer at Qualcomm; Thomas Quan, director at TSMC; and Murat Becer, vice president at Ansys. What follows are excerpts of that conversatio... » read more

The Uncertain Future Of In-Memory Compute


Experts at the Table — Part 2: Semiconductor Engineering sat down to talk about AI and the latest issues in SRAM with Tony Chan Carusone, chief technology officer at Alphawave Semi; Steve Roddy, chief marketing officer at Quadric; and Jongsin Yun, memory technologist at Siemens EDA. What follows are excerpts of that conversation. Part one of this conversation can be found here and part 3 is h... » read more

Testing ICs Faster, Sooner, And Better


The infrastructure around semiconductor testing is changing as companies build systems capable of managing big data, utilizing real-time data streams and analysis to reduce escape rates on complex IC devices. At the heart of these tooling and operational changes is the need to solve infant mortality issues faster, and to catch latent failures before they become reliability problems in the fi... » read more

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