SK Hynix CXL 2.0 Type 3 128GB Memory Expander Module

The SK Hynix CXL 2.0 Type 3 128GB Memory Expander Module (HMCG92AGBRA115N) is a standards-compliant Compute Express Link memory expansion device designed to extend the addressable memory capacity of CXL-enabled host systems beyond the physical DIMM slot constraints of conventional server platforms. Built on the CXL 2.0 specification and operating as a CXL.mem Type 3 device, the module attaches to the host CPU via a PCIe 5.0 x8 interface and presents a coherent, load/store-accessible memory pool that the host operating system can address as system memory. This architecture allows memory capacity to scale independently of compute resources, a critical capability for workloads whose working sets consistently exceed installed DRAM headroom.

The module incorporates SK Hynix DDR5 DRAM as its underlying memory medium, delivering the bandwidth and latency characteristics required for enterprise data-intensive operations. The CXL 2.0 protocol layer enables host-managed device memory (HDM) semantics, supporting both direct and pooled memory access modes as defined by the CXL Consortium specification. Form factor is the standard EDSFF E3.S or equivalent CXL add-in card format appropriate to this product line, enabling deployment in CXL-ready rack servers from major platforms. The module's memory controller handles ECC transparently, preserving data integrity at scale without host-side software overhead.

Enterprise infrastructure teams deploying this module gain a practical path to terabyte-scale per-node memory configurations without waiting for next-generation DIMM slot counts or CPU socket expansion. The device is particularly well suited to AI inference serving, in-memory database engines, large-scale analytics runtimes, and memory-intensive virtualization consolidation scenarios where aggregate memory bandwidth and capacity are primary constraints on throughput and job completion time. SK Hynix's CXL memory expander lineup is engineered to meet the reliability, availability, and serviceability expectations of production datacenter environments.

Ideal for

• Expanding per-node memory capacity in AI inference servers handling large language model weight sets that exceed native DIMM slot limits
• Scaling in-memory database instances (SAP HANA, Redis, VoltDB) to accommodate growing hot datasets without additional server nodes
• Increasing memory headroom in high-density VM consolidation environments to reduce VM sprawl and lower per-workload infrastructure footprint
• Supporting large-scale real-time analytics engines (Apache Spark, Presto) where aggregate working-set size directly constrains query parallelism
• Enabling memory pooling architectures in composable infrastructure deployments where CXL fabric allows dynamic memory allocation across compute nodes
• Augmenting memory capacity in HPC preprocessing and data staging nodes handling large genomics, financial risk, or simulation datasets

Technical specifications

Available from Omnixon Global. Submit an RFQ and our team will confirm configuration and availability for your order.