HPE 64GB (1x64GB) Dual Rank x4 DDR4-2666 CAS-19-19-19 Load Reduced Smart Memory Kit

The HPE 64GB (1x64GB) Dual Rank x4 DDR4-2666 CAS-19-19-19 Load Reduced Smart Memory Kit (838085-B21) is a high-capacity, enterprise-grade LRDIMM module engineered for HPE ProLiant Gen10 servers. Operating at DDR4-2666 MHz with a CAS latency of 19-19-19, this module delivers a balance of high bandwidth and reliable performance across memory-intensive server workloads. The Load Reduced (LRDIMM) architecture employs a memory buffer to reduce the electrical load on the memory bus, enabling higher memory capacities per system while maintaining signal integrity at speed.

As an HPE Smart Memory module, this kit incorporates an onboard Serial Presence Detect (SPD) mechanism that allows HPE ProLiant server firmware to identify, validate, and optimize the module automatically during POST. This Smart Memory technology enables HPE servers to run at the highest supported speeds for the installed configuration and provides enhanced error detection and platform telemetry. The x4 DRAM device width combined with dual-rank organization maximizes memory density within a single DIMM slot, making it well suited for platforms requiring large aggregate memory footprints without fully populating all available slots.

Designed for deployment in HPE ProLiant Gen10 server platforms including the DL380 Gen10, DL360 Gen10, DL560 Gen10, and DL580 Gen10, this module addresses the demands of modern datacenter, virtualization, in-memory database, and AI/ML infrastructure environments. It supports ECC (Error Correcting Code) functionality natively, providing the fault resilience required for mission-critical enterprise operations and continuous availability workloads.

Ideal for

• Large-scale virtualization environments running VMware vSphere or Microsoft Hyper-V, where maximizing virtual machine density per host requires high-capacity LRDIMM configurations
• In-memory database deployments such as SAP HANA, Oracle In-Memory, or Microsoft SQL Server In-Memory OLTP, where entire datasets must reside in RAM for sub-millisecond query response
• AI and machine learning inference or training nodes where large model parameters and datasets need to be staged in system memory alongside GPU or accelerator workloads
• High-performance computing (HPC) clusters and scientific simulation workloads that demand both high memory bandwidth and large per-node memory capacity
• Enterprise private cloud infrastructure running OpenStack or VMware Cloud Foundation, where consistent memory performance and ECC reliability are required across tenant workloads
• Big data analytics platforms such as Apache Spark running in-memory computation frameworks, requiring substantial DRAM capacity to cache and process large distributed datasets

Technical specifications

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