Liquid cooling is proving effective at cooling high-power chips, such as GPUs, but it’s creating thermal issues for other nearby chips that previously benefited from the airflow ...
High‑NA EUV's reduced field size is driving new innovation in optical proximity correction and mask synthesis.
Based CPU-GPU Architecture with Replay-Driven Simulation and Emulation,” was published by researchers at Intel, Nvidia and ...
Moore’s Law has shifted toward advanced packaging over the past few years, but the limits of that approach are just now coming into focus. AI and HPC designs are growing larger ...
As ATE systems become increasingly complex and data-intensive, traditional rule-based optimization methods struggle to keep ...
Inferencing at the edge has very different needs than training large language models or large-scale inferencing in AI data ...
Analysis of the Evolving Landscape of Ultra-low-power Edge AI Processors (U. of Austria, ETH Zurich)
A new technical paper, “Performance Analysis of Edge and In-Sensor AI Processors: A Comparative Review,” was published by University of Austria and ETH Zurich. Abstract “This review examines the ...
AI data centers are starting to replace copper with co-packaged optics in an effort to reduce energy consumed per bit and ...
A new technical paper, “Towards Structured Training and Validation of AI-based Systems with Digital Twin Scenarios,” was ...
AI workloads require rapid access to vast amounts of data, made possible by integrating HBMs. This approach, combining two, ...
An Experimental Methodology for Quickly Discovering the Reliable Read Disturbance Threshold of Real DRAM Chips,” was published by ETH Zurich and Rutgers University. Abstract “State-of-the-art DRAM ...
Three AI data center scaling strategies are scale-up, scale-out, and scale-across. Scale-up is within a rack; scale-out is ...
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