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Hynix HMA82GR7MFR8N-UHTD 16GB DDR4-2400MHz RDIMM 2Rx8 CL17 Memory
- 16GB capacity
- DDR4 SDRAM technology
- Registered DIMM (RDIMM) form factor
- Speed: 2400MHz (PC4-19200)
- CAS Latency: CL17
- Dual Rank (2Rx8)
- ECC (Error-Correcting Code) support
- Designed for server and workstation applications
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Product Overview
The Hynix HMA82GR7MFR8N-UHTD is a 16GB DDR4 RDIMM memory module designed for servers and high-performance workstations. It operates at 2400MHz with a CL17 latency, offering reliable and efficient data processing capabilities.
Technical Information
| Memory Size | 16GB |
| Memory Type | DDR4 SDRAM |
| Form Factor | RDIMM (Registered DIMM) |
| Speed | 2400MHz |
| CAS Latency | CL17 |
Additional Specifications
| Rank | 2Rx8 |
| ECC | Yes |
| Manufacturer | Hynix |
| Part Number | HMA82GR7MFR8N-UHTD |
Product Description
The Hynix HMA82GR7MFR8N-UHTD is a high-performance 16GB Registered Dual In-line Memory Module (RDIMM) that utilizes DDR4 SDRAM technology. Operating at a speed of 2400MHz, this module is designed to enhance the memory capacity and processing power of compatible server and workstation systems. The RDIMM format includes onboard registers that help reduce electrical load on the memory controller, improving stability and allowing for higher memory densities. This module features a CAS Latency (CL) of 17, indicating the number of clock cycles required to access a particular column of data. The 2Rx8 configuration signifies that the module has two ranks, each with eight data chips, which can improve performance by allowing the memory controller to interleave access between ranks. Furthermore, it incorporates Error-Correcting Code (ECC) functionality, which detects and corrects single-bit errors, crucial for maintaining data integrity in mission-critical applications where reliability is paramount. Designed for demanding computing environments, the HMA82GR7MFR8N-UHTD is an ideal upgrade for servers, workstations, and other systems requiring substantial and reliable memory resources. Its specifications make it suitable for memory-intensive tasks such as virtualization, large database operations, scientific computing, and content creation, ensuring smooth and efficient operation.



