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Hynix HMA84GL7MMFR4N-TFTE 32GB DDR4-2133MHz LRDIMM 4Rx4 CL15 Memory
- 32GB DDR4 LRDIMM Memory Module
- Speed: 2133MHz (PC4-17000)
- Latency: CL15
- Configuration: 4 Ranks x 4 Bits (4Rx4)
- Voltage: Standard DDR4 voltage
- ECC: Registered ECC (Error Correcting Code)
- Load-Reduced DIMM (LRDIMM) for higher density
- Optimized for server and data center environments
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Product Overview
The Hynix HMA84GL7MMFR4N-TFTE is a 32GB DDR4 LRDIMM memory module designed for high-density server applications. It operates at 2133MHz with a CL15 latency, offering excellent performance and stability for demanding enterprise workloads.
Technical Information
| Capacity | 32GB |
| Memory Type | DDR4 SDRAM |
| Form Factor | LRDIMM (Load-Reduced DIMM) |
| Speed | 2133MHz |
Additional Specifications
| CAS Latency | CL15 |
| Rank | 4Rx4 |
| ECC | Registered ECC |
Product Description
This Hynix LRDIMM module offers a substantial 32GB capacity, specifically engineered for server environments that require high memory density and reliability. The DDR4 standard provides improved performance and power efficiency over previous DDR generations. The Load-Reduced DIMM (LRDIMM) architecture is crucial for achieving higher memory capacities per channel by reducing the electrical load on the memory controller, enabling systems to support more DIMMs and thus more total memory. The module operates at a speed of 2133MHz (PC4-17000), a standard frequency for many server platforms, offering a good balance of performance and compatibility. Its CAS Latency is CL15, which is relatively low for DDR4, contributing to faster data access times. The 4Rx4 rank configuration signifies a high-density organization, with four ranks each comprising four data bits, further enhancing the module's performance potential by increasing the number of available memory banks. As a Registered ECC (Error Correcting Code) module, the HMA84GL7MMFR4N-TFTE provides enhanced data integrity, essential for mission-critical server operations. The onboard register buffers address and command signals, reducing the strain on the memory controller and allowing for greater system stability, especially in systems populated with many memory modules. This makes it an ideal choice for demanding enterprise workloads, including virtualization, large-scale data processing, and cloud computing infrastructure.
