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HP 6CN24AV 128GB Kit (4x32GB) DDR4-2933MHz RDIMM 2Rx4 CL21 Memory
- Total Capacity: 128GB
- Module Configuration: 4x 32GB DIMMs
- Memory Type: DDR4
- Form Factor: RDIMM (Registered DIMM)
- Speed: 2933MHz
- Latency: CL21
- Rank: 2Rx4 (Dual Rank x4)
- Compatibility: HP Servers and Workstations
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Product Overview
This HP memory kit includes four 32GB RDIMM modules, totaling 128GB of DDR4 memory. Operating at 2933MHz with CL21 latency, it's designed for high-performance servers and workstations.
Technical Information
| Total Capacity | 128GB |
| Module Size | 32GB |
| Number of Modules | 4 |
| Memory Type | DDR4 |
| Form Factor | RDIMM |
Additional Specifications
| Speed | 2933MHz |
| CAS Latency | CL21 |
| Rank | 2Rx4 |
| Manufacturer | HP |
| Part Number | 6CN24AV |
Product Description
The HP 6CN24AV is a high-capacity memory kit designed to significantly enhance the performance of compatible HP servers and workstations. This kit provides a total of 128GB of memory, distributed across four 32GB Registered DIMM (RDIMM) modules. RDIMMs are crucial for enterprise environments as they include a register that buffers memory commands and addresses, reducing electrical load on the memory controller and allowing for higher memory capacities and speeds. The memory operates at a DDR4 standard, offering improved bandwidth and power efficiency over previous DDR generations. With a speed of 2933MHz, it ensures rapid data processing, which is vital for memory-intensive applications such as virtualization, large databases, scientific simulations, and complex data analytics. The CL21 CAS latency indicates the number of clock cycles required to access data, providing a measure of the memory's responsiveness. The 2Rx4 designation signifies that each 32GB module is dual-ranked with x4 (4-bit wide) memory chips. Dual-rank modules can offer performance benefits by allowing the memory controller to access different ranks independently, effectively doubling the number of available memory banks. This kit is an ideal upgrade for systems requiring substantial memory resources to handle demanding workloads and improve overall system responsiveness and multitasking capabilities.
