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| Product Overview |
|---|
The P11448-ZA1 HPE 256GB DDR4-3200 Load-Reduced DIMM features octal rank x4 configuration, CAS latency 26-22-22, and 3D Stacked technology to deliver high-density, high-performance memory optimized for enterprise-class servers. |
| General Information | |
|---|---|
| Brand | HPE |
| Part Number | P11448-ZA1 |
| Technical Information | |
|---|---|
| Memory Capacity | 256GB |
| Memory Technology | DDR4 |
| Module Type | LRDIMM |
| RAM Standard | PC4-25600 |
| Pin Count | 288-Pin |
| Error Correction | ECC |
| Rank | Octal |
| Voltage | 1.2V |
| Performance | |
|---|---|
| Bus Speed | 3200 MT/s |
| Bandwidth | 25600 MB/s |
| Native Speed | 3200 MHz |
| CAS | 26 |
| Physical Characteristics | |
|---|---|
| Package | FBGA |
| Weight | 0.50 |
| Condition | Refurbished |
| Miscellaneous | |
|---|---|
| Eco Friendly | Yes |
| Assembly Required | No |
| Product Description |
|---|
The P11448-ZA1 HPE 256GB DDR4-3200 Octal Rank x4 CAS-26-22-22 Load-Reduced 3DS Memory is engineered to provide high-density memory solutions for enterprise servers. This module uses advanced 3D Stacked (3DS) technology to deliver increased capacity while maintaining efficient power consumption and thermal performance. Typically found in HPE servers requiring large memory pools, this Load-Reduced DIMM (LRDIMM) is ideal for data centers and cloud computing environments where reliability and scalability are critical. IT administrators and system architects benefit from its high capacity and speed, enhancing overall server performance. Key Features
This memory module supports intensive workloads such as virtualization, large databases, and in-memory analytics. Its robust design ensures stability and performance in demanding server environments, making it a reliable choice for expanding memory infrastructure. |
| Use Cases |
|---|
This memory module is suitable for environments requiring large memory capacities and high throughput. How It's Used:
By integrating this module, organizations can improve system responsiveness and support growing data demands efficiently. |