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Hynix HMAA4GU7AJR8N-XNT0AD 32GB DDR4-3200MHz UDIMM 2Rx8 CL22 Memory
- 32GB DDR4 SDRAM capacity.
- Unbuffered DIMM (UDIMM) form factor.
- Operating speed of 3200MHz (PC4-25600).
- CAS Latency (CL) of 22.
- 2Rx8 module configuration (dual rank, 8 bits wide).
- Suitable for high-performance desktops and workstations.
- Non-ECC memory module.
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Product Overview
The Hynix HMAA4GU7AJR8N-XNT0AD is a 32GB DDR4 UDIMM memory module, operating at 3200MHz with a CL22 latency. It is designed for high-capacity, high-speed performance in desktop and workstation systems.
Technical Information
| Memory Type | DDR4 SDRAM |
| Capacity | 32GB |
| Form Factor | UDIMM (Unbuffered DIMM) |
| Speed | 3200MHz |
Additional Specifications
| CAS Latency | CL22 |
| Rank | 2Rx8 |
| Brand | Hynix |
| Part Number | HMAA4GU7AJR8N-XNT0AD |
Product Description
The Hynix HMAA4GU7AJR8N-XNT0AD is a high-capacity 32GB DDR4 Unbuffered DIMM (UDIMM) memory module, engineered for systems that demand significant memory resources and high speeds. Running at an impressive 3200MHz, this module offers excellent bandwidth, which is crucial for demanding tasks such as gaming, video editing, 3D rendering, and running multiple virtual machines. The UDIMM form factor is standard for most desktop computers and workstations, providing direct signaling to the memory controller without buffering. This module features a CAS Latency (CL) of 22, representing the number of clock cycles between issuing a read command and the data becoming available. The 2Rx8 configuration indicates a dual-rank design, where the memory is organized into two ranks, each 8 bits wide. Dual-rank modules can sometimes offer a slight performance advantage over single-rank modules due to the memory controller's ability to interleave access between ranks, although this can depend on the specific system architecture. With its substantial 32GB capacity and high 3200MHz speed, the HMAA4GU7AJR8N-XNT0AD is an ideal choice for users looking to upgrade their desktop or workstation for enhanced multitasking capabilities and improved performance in memory-intensive applications. It provides a significant boost for users who frequently work with large datasets or complex software.
