Data movement has become an important concern in modern AI data centers. In the past, a cluster of a few servers could adequately handle back-office applications and databases. But with AI’s gigantic models, all sections of the data center need to move and receive data at high speeds.
That requires a lot more power use than in the past. GPU- and XPU-based systems are approaching 120KW per rack, and switching and networking components consume approximately 15-25% of total rack power, making low-power switch silicon a strategic requirement.
The Teralynx T100 delivers up to 25% lower power consumption than competitive solutions at a higher data rate. This enables AI infrastructures to deploy more accelerators within existing power envelopes without requiring additional power infrastructure.
“As AI workloads evolve and scale exponentially, hyperscalers require network architectures that optimize latency, power and scalability simultaneously,” said Rishi Chugh, vice president and general manager of the data center switch business unit at Marvell, in a statement.
