The Hynix HYMP351F72AMP4D2-Y5 is a 4GB DDR3 ECC Registered server memory module designed for servers and high-performance workstations. It improves system stability and reliability by using ECC (Error-Correcting Code) to detect and correct memory errors, which helps to prevent data corruption and system crashes. Registered memory, often called buffered memory, includes a register between the DRAM modules and the system's memory controller. This register reduces the electrical load on the memory controller, allowing servers to utilize more memory modules and expand overall memory capacity.
Applications
- Servers
- High-Performance Workstations
- Data Centers
- Cloud Computing
- Virtualization
Features
- 4GB Capacity
- DDR3 Technology
- ECC (Error-Correcting Code)
- Registered (Buffered)
- PC3-10600 (1333MHz) Speed
- 240-Pin DIMM
Benefits
- Increased System Stability: ECC corrects memory errors, preventing system crashes and data corruption.
- Greater Memory Capacity: The registered design enables higher memory density in server configurations to handle larger workloads.
- Enhanced Data Integrity: ECC ensures that data stored in memory is accurate and reliable through error correction.
- Faster Data Transfer: DDR3 technology offers quicker data transfer rates compared to older memory types.
- Optimized for Server Environments: Specifically designed and rigorously tested to meet the high demands of server environments.
Additional Details
The HYMP351F72AMP4D2-Y5 operates at a speed of 1333MHz (PC3-10600) and utilizes a 240-pin DIMM, the standard form factor for DDR3 memory. It typically operates at a voltage of 1.5V. Employing ECC Registered memory significantly enhances the reliability and uptime of servers, making it well-suited for business-critical applications and data centers. It is engineered to meet JEDEC standards, guaranteeing compatibility across various server platforms. It is frequently used in servers to manage large datasets and computationally intensive tasks, providing continuous and reliable performance even under substantial workloads.