FMS 2026: CXL 3.2 and liquid-cooled SSDs target AI-intensive data centers
The FMS 2026 conference highlighted advancements in CXL 3.2, MRDIMMs, and liquid-cooled SSDs designed to support high-performance computing in AI data centers. These storage and memory innovations are essential for scaling the infrastructure used in data-intensive streaming workloads and professional video processing.
Key Takeaways
- Xcena's MX1 computational CXL board integrates 3,072 RISC-V cores and supports 2 TB of DDR5 DRAM for near-data processing.
- Solidigm's D7-PS1010 SSD uses a spring-loaded cold plate for liquid-flow-through cooling within a 9.5-mm E1.S form factor.
- New MRDIMM technology uses multiplexed buffer registers to hide DRAM die, increasing total bandwidth and capacity on DDR5 modules.
- CXL 3.2 support on the MX1 board enables x8 PCIe Gen 6.0 interfaces with LZ4 hardware-based memory compression.
- Embedded systems are transitioning from SATA to NVMe and EDSFF standards while still maintaining support for legacy eMMC and DDR3.
Why It Matters
The transition to CXL 3.2 and liquid-cooled storage marks a fundamental shift in how streaming infrastructure handles the massive datasets required for AI-driven recommendation engines and real-time video transcoding. By moving compute closer to data via RISC-V cores on CXL boards, operators can reduce the latency overhead of traditional CPU-to-memory paths. As hardware-level memory compression and pooling become standard, the ecosystem will see improved utilization of existing DRAM investments, helping to mitigate high procurement costs in a volatile supply chain. Watch for the commercial adoption of CXL memory pooling in hyperscale cloud environments by the end of 2026.
Additional Context
The shift toward advanced memory architectures is largely a response to the 'memory wall' bottleneck in generative AI and high-performance computing. Per Samsung and SK hynix reporting in July 2026, CXL-based memory expansion can increase total system memory capacity by up to 50% while doubling bandwidth compared to standard DDR5 configurations. These manufacturers are currently prioritizing CXL 3.2-based modules to create a new 'Inference Memory Tiering' architecture, which SK hynix claims can improve AI inference efficiency by over 35% compared to legacy server designs. Concurrent with hardware innovation, the global memory market is facing significant pricing pressure. According to Fusion Worldwide data from June 2026, mainstream 64GB DDR5 RDIMM prices have spiked due to intense demand from hyperscale data centers and AI clusters, occasionally resulting in OEM servers shipping without memory installed as allocation struggles to keep pace. Analysts at Counterpoint Research projected in mid-2026 that server-related products would account for approximately 56% of total global memory sales for the year, up from 37% in 2025, signaling that AI infrastructure spending has replaced consumer electronics as the primary driver of semiconductor revenue. Thermal management has also become a critical design constraint for next-generation racks. Per Solidigm and Supermicro in September 2025, the D7-PS1010 liquid-cooled SSD was specifically developed for fanless server environments like the NVIDIA GB300 NVL72. By utilizing direct-to-chip liquid cooling, these units can reduce cooling energy requirements by up to 84% compared to traditional air-cooled E1.S drives. This trend toward liquid-cooled storage is essential for maintaining consistent IOPS in the high-density configurations required for modern video delivery and AI factories.
Read full article at electronicdesign.com
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