Samsung CXL DRAM Module CMM-D 128GB

The Samsung CXL DRAM Module CMM-D 128GB (M6IKR8G4ZBFQ-50A73) is a Compute Express Link (CXL) 2.0-compliant memory expansion module built on Samsung's enterprise-grade DRAM architecture. Designed to extend system memory capacity beyond traditional DIMM slot constraints, it connects via a CXL 1.1/2.0 interface over a PCIe Gen 5 x8 host link, enabling host processors to access pooled memory resources with coherent, cache-coherent semantics. The module delivers 128GB of usable DRAM capacity in a standard E3.S or EDSFF form factor, making it suited for memory-constrained server environments where per-socket DIMM slot counts limit addressable memory.

The CMM-D architecture implements CXL.mem protocol, allowing the host CPU to treat the module's DRAM as directly load/store addressable memory through the CXL fabric. This design is distinct from storage-class or persistent memory solutions — the CMM-D provides volatile DRAM semantics with latency characteristics that, while slightly higher than local DDR5 channels due to the PCIe/CXL traversal overhead, remain well within ranges appropriate for memory-capacity-bound workloads. Samsung's CMM-D series leverages DDR5 DRAM dies internally, inheriting the bandwidth and density advantages of that generation.

Targeted at hyperscale datacenters, cloud service providers, and enterprise AI/ML infrastructure operators, the Samsung CMM-D 128GB enables memory pooling and tiering strategies that allow a single server to address significantly larger working sets than its native DIMM slots permit. This is particularly relevant for in-memory databases, large language model inference serving, high-performance analytics, and virtualization platforms where memory capacity — rather than raw compute — is the primary scaling bottleneck. The module is compatible with CXL-enabled Intel Xeon Scalable (Sapphire Rapids and later) and AMD EPYC (Genoa and later) processors.

Ideal for

• In-memory database scaling: expanding addressable DRAM for platforms such as SAP HANA, Redis, or Oracle TimesTen beyond native DIMM slot limits on a single server node
• Large language model (LLM) inference serving: providing additional memory capacity to hold large model weight tensors in DRAM for AI inference accelerator-attached server configurations
• Virtualization and cloud-native density: increasing per-host memory capacity in VMware vSphere, Red Hat OpenShift, or KVM environments to support higher virtual machine or container density
• High-performance analytics and data warehousing: enabling large working-set analytics engines (Apache Spark, ClickHouse, Vertica) to operate entirely in memory without spilling to NVMe
• CXL memory pooling and tiering architectures: participating in disaggregated memory pool topologies where CXL switches allow multiple hosts to share or dynamically allocate memory resources
• Genomics and scientific computing: supporting memory-intensive bioinformatics pipelines and simulation workloads that require multi-terabyte addressable memory across clustered compute nodes

Technical specifications

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