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Hynix HMA84GR7MFR4N-VKT3 32GB DDR4-2666MHz RDIMM 2Rx4 CL19 Memory
- Capacity: 32GB
- Type: DDR4 SDRAM
- Form Factor: RDIMM (Registered DIMM)
- Speed: 2666MHz (PC4-21300)
- CAS Latency: CL19
- Organization: 2Rx4 (Dual Rank, x4)
- ECC: Yes (Error-Correcting Code)
- Designed for enterprise server applications
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Product Overview
This Hynix 32GB DDR4 RDIMM memory module operates at 2666MHz with a CL19 latency. It features a 2Rx4 organization and ECC support, making it ideal for enterprise servers requiring high capacity and reliability.
Technical Information
| Capacity | 32GB |
| Memory Type | DDR4 SDRAM |
| Form Factor | RDIMM |
| Speed | 2666MHz |
Additional Specifications
| CAS Latency | CL19 |
| Rank | 2Rx4 |
| ECC | Yes |
Product Description
The Hynix HMA84GR7MFR4N-VKT3 is a 32GB DDR4 Registered DIMM (RDIMM) memory module engineered for high-performance enterprise server environments. It operates at a frequency of 2666MHz, providing substantial bandwidth to support demanding workloads such as virtualization, database management, and complex data analytics. The Registered DIMM architecture includes an onboard buffer that reduces the electrical load on the memory controller, enabling greater memory density and improved system stability, which is crucial for servers running multiple applications simultaneously. This module is configured as 2Rx4, indicating it is dual-rank with four memory chips per rank. This configuration can enhance performance by allowing the memory controller to interleave operations between ranks. The CAS Latency (CL) is set at CL19, a common specification for DDR4 memory at this speed, ensuring efficient data access and processing. Equipped with Error-Correcting Code (ECC) capabilities, this Hynix RDIMM can detect and correct single-bit errors and detect multi-bit errors, significantly reducing the risk of data corruption and system crashes. This feature is indispensable for mission-critical server operations where data integrity and uptime are paramount. The 32GB capacity offers a robust foundation for memory-intensive server tasks, contributing to overall system responsiveness and efficiency.
