Chip Industry Week In Review


Computex in Taiwan: Arm and Nvidia introduced an AI PC platform, RTX Spark, with an Arm-based Grace CPU, Blackwell RTX GPU, and unified memory. Cadence announced a fully autonomous virtual agentic AI design engineer, enabling customers to run dynamic simulations in automated workflows. Intel launched Xeon 6+, its first data-center CPU built on Intel Foundry's 18A process. The company... » read more

Chip Industry Week In Review


Advanced nodes and packaging AMD announced more than $10B in Taiwan ecosystem investments to scale advanced packaging manufacturing for AI infrastructure. The effort includes EFB-based 2.5D packaging collaborations with ASE and others. AMD also announced the start of its production ramp of its Venice processors on TSMC's 2nm process. Lam Research established a panel-level packaging cen... » read more

AI Growing Impact On Chip Design And EDA Tools


Key Takeaways Many workflows in the data center are customer-specific, which is part of the reason there is so much interest in agentic AI-enabled tools. Large systems companies are pressing EDA vendors for performance improvements to keep pace with their AI workflows. The makeup of design teams is changing as AI infiltrates more of the chip design process. Experts at the Ta... » read more

DRAM’s Whac‑A‑Mole Security Crisis


Key takeaways: Rowhammer remains a DRAM security threat, while Rowpress has increasingly become a related threat. New commands issued by the memory controller can help manage refreshes, but they’re not a perfect solution. A smaller, vertical DRAM cell may eliminate the problem, but it’s years away. Rowhammer has been a persistent DRAM issue across several memory generati... » read more

AI’s Potential And Limitations In Chip Design


Experts at the Table: Semiconductor Engineering sat down to discuss the opportunities and challenges of using AI in chip design, with Thomas Andersen, vice president for AI & Machine Learning at Synopsys; Sridhar Boinapally, senior director of analog/mixed signal tools/flow at Intel; Alex Starr, corporate fellow at AMD; Stuart Oberman, vice president for GPU hardware engineering at Nvidia; ... » read more

Chip Industry Technical Paper Roundup: Mar. 31


New technical papers recently added to Semiconductor Engineering’s library: Technical Paper Research Organizations DiscoRD: An Experimental Methodology for Quickly Discovering the Reliable Read Disturbance Threshold of Real DRAM Chips 🔗 ETH Zurich, Rutgers University Performance Analysis of Edge and In-Sensor AI Processors: A Comparative Review 🔗 Univ... » read more

Chip Industry Week In Review


Arm uncorked its first internally developed CPU chip this week, aimed squarely at the agentic AI data center market. Arm CEO Rene Haas (pictured) emphasized the CPU's power efficiency and performance/watt compared to other AI processor architectures. "We are obsessed with efficiency, and if you think about one of the biggest appeals that Arm has had over the years, it is power profile," he ... » read more

How SW and HW Vulnerabilities Can Complement LLM-Specific Algorithmic Attacks (UT Austin, Intel et al.)


A new technical paper, "Cascade: Composing Software-Hardware Attack Gadgets for Adversarial Threat Amplification in Compound AI Systems," was published by the University of Texas, Austin, Intel Labs, Symmetry Systems, Microsoft and Georgia Tech. Abstract "Rapid progress in generative AI has given rise to Compound AI systems - pipelines comprised of multiple large language models (LLM), so... » read more

Chip Industry Week in Review


The IEEE ISSCC conference was held this week in San Francisco. Among the highlights: IBM detailed an AI accelerator based on its new inferencing dataflow architecture. CEA-Leti presented a chip-scale, ultra-fast, battery-operated EPR spectrometer. QuTech introduced a cryo-CMOS SoC with NV centers in diamond. UTokyo showed its low-jitter PLL architecture for beyond 5G/6G. Imec d... » read more

Can A Computer Science Student Be Taught To Design Hardware?


Key Takeaways New approaches are being devised and tested to address the talent shortage. Leveraging AI in design tools will help engineers become more efficient, and potentially could reduce the time it takes to train engineering students. EDA companies are looking at whether it's possible to train computer science and software engineers to become hardware engineers. A vari... » read more

← Older posts