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The Cisco E100S-MEM-UDIMM8G= is an 8GB Unbuffered Dual Inline Memory Module (UDIMM) designed for Cisco’s enterprise and data center hardware. Operating at 2133 MT/s (DDR4-2133) with a 1.2V low voltage profile, this module balances performance and power efficiency for memory-intensive workloads. Unlike Registered DIMMs (RDIMMs), UDIMMs prioritize low latency over maximum capacity, making them ideal for applications requiring rapid data access.
The E100S-MEM-UDIMM8G= is validated for use in:
For VMware ESXi or Hyper-V clusters, the module’s low latency ensures minimal overhead during VM migrations or snapshot operations.
Applications like SAP HANA or Redis benefit from unbuffered memory’s direct access to the memory controller, reducing query response times by 12–18% compared to RDIMMs (based on Cisco benchmarks).
In IoT or 5G edge deployments, the 1.2V power profile reduces thermal stress in compact, fanless enclosures.
Pair 4–8 E100S-MEM-UDIMM8G= modules with RDIMMs in UCS C240 M5 servers to allocate unbuffered memory for latency-sensitive tasks (e.g., real-time analytics) and RDIMMs for bulk storage.
For SMBs, using 8GB UDIMMs instead of 16GB RDIMMs cuts hardware costs by 30–40% while maintaining performance for light virtualization.
Cisco enforces strict population rules:
Update the server’s CIMC and BIOS to the latest versions. For example, UCS C220 M5s require BIOS 4.1(3a)+ for stable DDR4-2133 support.
If the system flags “underutilized memory,” disable memory RAS features (e.g., sparing) in BIOS for non-mission-critical workloads.
To avoid counterfeit risks, purchase from verified suppliers like itmall.sale’s Cisco memory catalog. Authentic modules include a Cisco Unique Device Identifier (UDI) sticker and are pre-flashed with Cisco-specific SPD data.
While 32GB/64GB RDIMMs dominate hyperscale environments, the E100S-MEM-UDIMM8G= remains relevant for edge deployments and budget-focused upgrades. Its plug-and-play simplicity and optimized latency make it a pragmatic choice for enterprises balancing performance and TCO. However, for AI/ML workloads requiring 256GB+ per node, consider Cisco’s 64GB LRDIMMs or Optane Persistent Memory.
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