Chip Companies Play Bigger Role In Shaping University Curricula


A shortage of senior engineers with the necessary skills and experience is forcing companies to hire and train fresh graduates, a more time-consuming process but one that allows them to rise through the ranks using the companies' preferred technology and systems. Universities and companies share the goal of helping a graduate become productive in the workplace as quickly as possible, and the... » read more

Top-Down Vs. Bottom-Up Chiplet Design


Chiplets are gaining widespread attention across the semiconductor industry, but for this approach to really take off commercially it will require more standards, better modeling technologies and methodologies, and a hefty amount of investment and experimentation. The case for chiplets is well understood. They can speed up time to market with consistent results, at whatever process node work... » read more

GenAI + Semiconductors + Humanity


Silicon Catalyst held its 2024 Semiconductor Industry Forum in Mountain View, CA, at the Computer History Museum on November 13th. Richard Curtin, managing partner for Si Catalyst, opened the event by thanking David House, vice chair of the Board at the Computer History Museum and creator of the 4004 processor, and the CHM staff for hosting the event. Richard talked about the start of se... » read more

Chip Industry Week In Review


SK hynix started mass production of 1-terabit  321-high NAND, with availability scheduled for the first half of next year. Rapidus will receive an additional ¥200 billion yen ($1.28B) from the Japanese government beginning in fiscal year 2025, reports Nikkei. This is on top of ¥920 billion yen ($5.98B) Rapidus has already received from the government in support of its goal to reach commer... » read more

Blog Review: Nov. 20


Siemens’ Jonathan Muirhead explains why matching and symmetry are so important for analog and RF circuits, especially in topological structures like differential pairs and current mirrors, and introduces checking techniques to ensure compliance. Cadence's Satish Kumar Padhi examines the significance of randomization in PCIe IDE verification, focusing on how it ensures data integrity and en... » read more

Managing The Huge Power Demands Of AI Everywhere


Before generative AI burst onto the scene, no one predicted how much energy would be needed to power AI systems. Those numbers are just starting to come into focus, and so is the urgency about how to sustain it all. AI power demand is expected to surge 550% by 2026, from 8 TWh in 2024 to 52 TWh, before rising another 1,150% to 652 TWh by 2030. Commensurately, U.S. power grid planners have do... » read more

Building Safe And Secure Software With Rust On Arm


The Rust Programming Language has gained the attention of government security agencies, and even the White House, due to its unique blend of safety, performance and productivity. Rust is designed to remove common programming burdens and handle issues like use-after-free errors at compile time. Remarkably, it achieves this without using a garbage collector, generating machine code that rivals th... » read more

Shift Left Is The Tip Of The Iceberg


Shift left is evolving from a buzzword into a much broader shift in design methodology and EDA tooling, and while it's still early innings there is widespread agreement that it will be transformative. The semiconductor industry has gone through many changes over the past few decades. Some are obvious, but others happen because of a convergence of multiple factors that require systemic change... » read more

New AI Data Types Emerge


AI is all about data, and the representation of the data matters strongly. But after focusing primarily on 8-bit integers and 32‑bit floating-point numbers, the industry is now looking at new formats. There is no single best type for every situation, because the choice depends on the type of AI model, whether accuracy, performance, or power is prioritized, and where the computing happens, ... » read more

A Comprehensive Guide to Understanding AI Inference on the CPU


As AI continues to revolutionize industries, new workloads, like generative AI, inspire new use cases, the demand for efficient and scalable AI-based solutions has never been greater. While training often garners attention, inference—the process of applying trained models to new data—is essential for AI workloads, whether they are running in the cloud, or enabling real-world applications at... » read more

← Older posts