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| Product Overview |
|---|
The P35426-001 HPE XL675d Gen10 Plus Accelerator Tray provides a high-density PCIe card deployment solution tailored for HPE Gen10 Plus servers, supporting both double and single wide accelerator cards with robust mechanical design to ensure reliability in demanding computing environments. |
| General Information | |
|---|---|
| Brand | HPE |
| Part Number | P35426-001 |
| Technical Information | |
|---|---|
| Interface / PCIe Slot | PCIe 4.0 x16 |
| Power Connector | Server Backplane |
| Physical Characteristics | |
|---|---|
| Slot Width | 10 Double-Width PCIe,16 Single-Width PCIe |
| Form Factor | Half-Height Half-Length (HHHL) |
| Weight | 3.00 |
| Condition | Refurbished |
| Product Description |
|---|
The P35426-001 HPE XL675d Gen10 Plus Accelerator Tray is engineered to provide high-density support for multiple PCIe accelerator cards within HPE Gen10 Plus server platforms. This tray accommodates up to 10 double wide and 16 single wide PCIe cards, enabling data centers and enterprises to scale their GPU and accelerator deployments efficiently. Commonly deployed in high-performance computing, AI, and data analytics environments, this accelerator tray enhances computational throughput by maximizing the number of installed accelerator cards without compromising system integrity or airflow. IT professionals and system integrators benefit from its streamlined design that simplifies hardware installation and maintenance. Key Features
This accelerator tray is a critical component for organizations seeking to expand their computational resources while maintaining efficient use of rack space. Its compatibility with HPE Gen10 Plus servers ensures seamless integration, helping to accelerate workloads across various industries. |
| Use Cases |
|---|
The P35426-001 HPE XL675d Gen10 Plus Accelerator Tray is ideal for environments requiring scalable and dense GPU or accelerator card installations. How It's Used:
This tray enables organizations to maximize their server accelerator capacity, improving computational density and efficiency in a variety of demanding applications. |