Emerging, data-intensive technologies like artificial intelligence and machine learning are gaining popularity. Data centers, which act as the essential infrastructure for these technologies, need to ...

Soaring AI/HPC device demand is driving leading-edge foundries to support the transition from wafers to panels to accommodate increasingly larger device sizes. But to ensure that panels with multiple ...

Researchers from Georgia Institute of Technology published a technical paper titled “Open DRAM Model—Part II: Enabling ...

Researchers from Rotonium, Centre for Quantum Technologies at National University of Singapore, Inveriant, Politecnico di Milano, and CNIT published a technical paper titled “Design and Benchmarking ...

Key Takeaways: There is no single processor capable of executing everything efficiently, meaning that multiple processors are required. Maximum efficiency is gained by minimizing the movement of data.

Quantum computing has imprinted itself on our society as a weird, wacky way of computing that most of us can’t comprehend.

Ethernet auto-negotiation; multiphysics to avoid overdesign; PCB design reuse; mobile LLM quantization; modeling BSPDNs.

As the semiconductor ecosystem pivots to AI, it is transforming how IP is created, verified, managed, and sold.

The conversation about agentic AI in semiconductor and PCB design tends to focus on capability: what the agent can do, how much time it saves, and which parts of the workflow it can automate. That is ...

AI infrastructure is entering a crucial new phase. The first phase of generative AI infrastructure was defined by accelerator scale: how many GPUs, NPUs or custom AI accelerators could be deployed, ...