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Product Overview |
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The 370-ACKQ Load Reduced DDR4 memory kit combines large capacity and error-correcting design to support servers needing reliable and extensive memory resources. It's well suited for enterprise servers and systems aiming to balance performance with power efficiency. |
General Information |
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| Brand | Dell |
| Part Number | 370-ACKQ |
Technical Information |
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| Memory Technology | DDR4 |
| Module Type | RDIMM |
| RAM Standard | PC4-17000 |
| Pin Count | 288-Pin |
| Error Correction | ECC |
| Rank | Quad Rank |
| Voltage | 1.2V |
Performance |
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| Bus Speed | 2133MHz |
| Bandwidth | 17000 MB/s |
| Native Speed | 2133MHz |
| CAS | CL15 |
Physical Characteristics |
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| Weight | 3.00 |
| Condition | Refurbished |
Miscellaneous |
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| Eco Friendly | Yes |
| Assembly Required | Yes |
Product Description |
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This Load Reduced DDR4 memory kit offers a total of 768GB capacity, configured as twelve 64GB RDIMM modules. It is built for servers that require large memory pools to handle intensive data workloads and virtualization tasks efficiently. Often found in enterprise data centers and high-performance computing environments, these RDIMMs help maintain system stability and data integrity thanks to ECC error correction. The quad rank layout supports enhanced reliability and data throughput. Key Features
Commonly deployed in rack servers and workstations, this memory kit plays a key role in managing heavy computational workloads. It helps ensure that mission-critical applications run smoothly without memory bottlenecks, especially in virtualization or database scenarios. |
Use Cases |
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The 370-ACKQ Load Reduced DDR4 memory modules are designed for enterprise-grade servers requiring substantial memory capacity and reliability. This memory kit is ideal for data centers and IT infrastructures focused on high-density virtualization, in-memory analytics, and mission-critical workloads that demand consistent error correction and power-efficient operation. How It's Used:
This memory solution facilitates scalable and efficient computing by reducing power draw while maintaining data integrity, making it suitable for complex server deployments where operational continuity and resource optimization are paramount. |