By Arifur Rahman, Director of Product Marketing, Custom Cloud Solutions, Marvell
AI and ML workloads are rewriting the rules of data center design. Memory demands are reaching an unprecedented level due to growing LLM sizes, expanding context windows and growing KV-cache requirements. Traditional servers are not architected to meet this surge. Memory has become the primary bottleneck constraining AI performance and infrastructure efficiency. CXL-based memory expansion has emerged as one of the definitive architectural answers, and Marvell is raising the bar.
Building on the strong market adoption of the first-generation Structera® X CXL controllers, the second-generation Structera X 3406 and Structera X 3506, co-developed and co-architected with leading hyperscalers, address the most demanding AI infrastructure requirements.
Modern AI inference workloads, from LLM serving to deep learning recommendation models (DLRM), are memory bound. KV-cache capacity determines time-to-first-token (TTFT), throughput and XPU utilization. When memory runs out, performance collapses.
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