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Hynix HMT84GL7AMR4A-PBM2-AF 32GB DDR3-1600MHz LRDIMM 4Rx4 CL11 Memory
- Capacity: 32GB
- Type: DDR3 SDRAM
- Form Factor: LRDIMM (Load-Reduced DIMM)
- Speed: 1600MHz (PC3-12800)
- Configuration: 4Rx4 (Quad Rank x4)
- Latency: CL11
- Voltage: 1.5V (typical)
- Designed for servers and high-performance workstations
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Product Overview
This Hynix 32GB DDR3 LRDIMM memory module operates at 1600MHz. It features a 4Rx4 configuration and CL11 latency, designed for high-capacity server and workstation applications.
Technical Information
| Capacity | 32GB |
| Type | DDR3 SDRAM |
| Form Factor | LRDIMM |
Additional Specifications
| Speed | 1600MHz |
| Rank | 4Rx4 |
| Latency | CL11 |
Product Description
The Hynix HMT84GL7AMR4A-PBM2-AF is a high-performance 32GB Load-Reduced Dual In-line Memory Module (LRDIMM) designed for demanding server and workstation environments. Operating at a speed of 1600MHz (also known as PC3-12800), this module provides substantial bandwidth for memory-intensive applications. LRDIMMs are specifically engineered to increase memory capacity and improve signal integrity in systems with a large number of memory slots, making them crucial for high-end servers and complex computing tasks. This module features a 4Rx4 organization, indicating it is quad-rank with each rank utilizing x4 (4-bit wide) data paths. This configuration allows for higher memory density and can improve performance in certain multi-processor or high-slot-count systems by distributing the memory load more effectively. The CAS Latency (CL) is rated at 11, which specifies the number of clock cycles required to access data after a command is issued. A CL11 rating at 1600MHz offers a good balance between speed and responsiveness. With its 32GB capacity, 1600MHz speed, and LRDIMM architecture, the HMT84GL7AMR4A-PBM2-AF is an ideal choice for memory upgrades in enterprise servers, cloud computing infrastructure, large-scale virtualization, and high-performance computing (HPC) environments. It ensures that systems can handle larger datasets and more concurrent operations efficiently, contributing to overall system stability and performance.
