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

Wide Band Gap—The Revolution In Power Semiconductors


New government regulations and industry standards are leading companies to adopt wide bandgap (WBG) power solutions, both to reduce their carbon footprint and to meet increasing demand for higher power systems aimed at electric vehicles, renewable energy, datacenters, and other markets. The automotive industry is one of the biggest markets driving demand for WBG power devices. The European U... » read more

Keeping The Balance


By Ann Steffora Mutschler The brains of datacenters today are more powerful than ever due to technology advancements in chip architectures and in manufacturing processes that allow more processing power thanks to Moore’s Law. But knowing exactly how and where to configure the processors and cores for optimum throughput and performance within a certain power budget raises a number of qu... » read more