Chip Industry Week In Review


Notable deals Cadence and Intel Foundry inked a multi-year agreement to advance design technology co-optimization and create PDKs for Intel Foundry's 14A process. Nvidia and SK hynix announced a multi-year partnership to co-develop memory technology for AI infrastructure and physical AI. Teradyne unveiled an integrated test cell solution with TEL that supports known-good device scree... » read more

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

Orbital Data Centers Are Souped-Up Satellites – For Now


Key Takeaways: Today’s orbital data centers are better described as compute centers in space, as they resemble satellite constellations more than terrestrial data centers. The most common power solution is sun-synchronous solar at the poles, but this requires a multi-hop data relay from power-hungry compute to standard satellite constellations in the low-orbit mesh, then to Earth. ... » read more

Chip Industry Technical Paper Roundup: May 26


New technical papers recently added to Semiconductor Engineering’s library: Technical Paper Research Organizations SHIP: SRAM-Based Huge Inference Pipelines for Fast LLM Serving 🔗 Nvidia, Groq Not All Thoughts Need HBM: Semantics-Aware Memory Hierarchy for LLM Reasoning 🔗 USC, University of Wisconsin-Madison Water-based, large-scale transfer of... » 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

Large-scale, SRAM-based LLM Inference Deployment (Groq)


A new technical paper, "SHIP: SRAM-Based Huge Inference Pipelines for Fast LLM Serving," was published by researchers at Nvidia, with work done while at Groq. Abstract "The proliferation of large language models (LLMs) demands inference systems with both low latency and high efficiency at scale. GPU-based serving relies on HBM for model weights and KV caches, creating a memory bandwidth b... » read more

Chip Industry Week in Review


Global The U.S. created a licensing path for Nvidia H200 shipments in January and has since approved sales to 10 Chinese companies, but so far no shipments have been confirmed, reports Reuters. With a looming end-of-year expiration, SIA, SEMI, and other business groups are urging Congress to extend the US semiconductor tax credit and expand it to cover semiconductor design and other act... » read more

Chip Industry Week In Review


Manufacturing ASE and WUS are jointly building a ~$1.1B advanced packaging hub in Kaohsiung, Taiwan, for fan-out chip-on-substrate (FOCoS) and flip-chip ball grid array (FC BGA) technologies. The new site is expected to be completed by September 2029. SpaceX filed documents for a “Terafab” semiconductor manufacturing and computing facility at Gibbons Creek Reservoir in Texas, with a... » read more

Humanoid Touch And Voice Are Improving Rapidly


Key Takeaways Humanoid robots are rapidly expanding beyond factories and logistics toward broader, general-purpose roles (including in-home assistance), driven by advances in AI and sensing. Compared with vision and language, touch (haptics) and hearing/voice in real environments remain the hardest — and most commercially important — sensing challenges, requiring fast sensor fusio... » read more

GPU Power Prediction Tool for AI Workloads (MIT, IBM)


A new technical paper, "EnergAIzer: Fast and Accurate GPU Power Estimation Framework for AI Workloads," was published by researchers at MIT and IBM Research. Abstract "As AI workloads drive increases in datacenter power consumption, accurate GPU power estimation is critical for proactive power management. However, existing power models face a scalability bottleneck not in the modeling tec... » read more

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