Intel teams up everywhere; GPU rowhammer attack; fast verification; Taiwan IC industry wants stockpiles; China poaches Taiwan ...
The number and variety of test interfaces, coupled with increased packaging complexity, are adding a slew of new challenges.
In the cloud, AI runs in a kind of computational luxury. Thousands of GPUs and CPUs sit in climate-controlled buildings with access to ample power and memory. Utilization may be inefficient—often just ...
As data rates continue to increase, maintaining reliable links requires careful coordination between the PHY and controller ...
Staying inside increasingly narrow process windows as specialty devices scale, diversify, and enter high-volume production.
A new technical paper, “Device/circuit simulations of silicon spin qubits based on a gate-all-around transistor,” was ...
Limitations—such as latency, bandwidth costs, privacy concerns, catastrophic consequences in the event of failure, and ...
Why latency guarantees, memory movement, power budgets, and rapid model deployment now matter more than raw TOPS.
InP and SiPho join CMOS as critical technologies. Lasers, CPO and OCS will be everywhere (indium phosphide, silicon photonics ...
What makes one AI chip better than another?
How next‑gen AI accelerators break past single‑chip limits using advanced IP, high‑speed interconnects, memory interfaces, ...
Processor architectures are evolving faster than ever, but they still lag the pace of AI development. Chip architects must ...
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