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Product Overview |
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The HPE P21674-001 memory module offers 32GB of DDR4 RAM operating at 3200MT/s with ECC support, designed primarily for servers that require reliable and fast memory. It fits into systems that comply with the PC4-25600 standard, providing stable performance for enterprise workloads. |
General Information |
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| Brand | HPE |
| Part Number | P21674-001 |
Technical Information |
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| Memory Capacity | 32GB |
| Memory Technology | DDR4 |
| Module Type | RDIMM |
| RAM Standard | PC4-25600 |
| Pin Count | 288-Pin |
| Error Correction | ECC |
| Rank | 2Rx4 |
| Voltage | 1.2V |
Performance |
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| Bus Speed | 3200MT/s |
| Bandwidth | 25600 MB/s |
| Native Speed | 3200 MT/s |
Physical Characteristics |
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| Weight | 0.50 |
| Condition | Refurbished |
Product Description |
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This 32GB DDR4 memory module is built for servers and workstations that demand stable and error-checked performance. Often found in enterprise environments, it supports error-correcting code (ECC) to reduce data corruption risks during intensive tasks. Commonly used in HPE systems, this memory is designed to handle high workloads and maintain system integrity. IT professionals and system administrators rely on such modules to ensure uptime and data accuracy in critical applications. Key Features
These memory modules are typically deployed in servers running databases, virtualization, or heavy computation. They play a key role in keeping systems running smoothly and preventing crashes due to memory errors. |
Use Cases |
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The HPE 32GB DDR4-3200MT/s 2Rx4 ECC PC4-25600 Memory module is designed for high-demand server environments where data integrity and fast processing are critical. It is ideal for IT infrastructure that supports virtualization, database management, and mission-critical applications requiring reliable and scalable memory solutions. How It's Used:
This memory module contributes to operational stability and scalability by providing error-correcting capabilities and high-speed data transfer rates. It enables organizations to maintain consistent performance levels while accommodating growth in memory-intensive applications. |