The opportunity for custom silicon isn’t just getting larger – it’s becoming more diverse.
At the Custom AI Investor Event, Marvell executives outlined how the push to advance accelerated infrastructure is driving surging demand for custom silicon – reshaping the customer base, product categories and underlying technologies. (Here is a link to the recording and presentation slides.)
Data infrastructure spending is now slated to surpass $1 trillion by 20281 with the Marvell total addressable market (TAM) for data center semiconductors rising to $94 billion by then, 26% larger than the year before. Of that total, $55.4 billion revolves around custom devices for accelerated compute1. In fact, the forecast for every major product segment has risen in the past year, underscoring the growing momentum behind custom silicon.
The deeper you go into the numbers, the more compelling the story becomes. The custom market is evolving into two distinct elements: the XPU segment, focused on optimized CPUs and accelerators, and the XPU attach segment that includes PCIe retimers, co-processors, CPO components, CXL controllers and other devices that serve to increase the utilization and performance of the entire system. Meanwhile, the TAM for custom XPUs is expected to reach $40.8 billion by 2028, growing at a 47% CAGR1.
And as demand for custom solutions grows among sovereign clouds, AI-centric service providers, and other customers, Marvell is actively engaged in 18 custom projects. These include 12 devices for the four major hyperscalers (three XPUs and nine XPU attach devices), and six devices for emerging AI customers (two XPUs and four XPU attach devices).
The rapid pace of innovation also means leapfrog advances in the materials, concepts and technologies for building accelerated infrastructure. Some of the ideas discussed in the session include:
But why repeat the whole event here. Get more at the link.
1Marvell estimates developed from forecasts from 650 Group, Cignal AI, Dell’Oro and other research firms.
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Tags: data centers, AI, AI infrastructure, custom computing, Optical Connectivity
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