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Dell CN-0GHV6W GPU Expansion Riser Board for PowerEdge C4130
- Designed for Dell PowerEdge C4130 server chassis.
- Enables expansion for GPU modules.
- Provides necessary PCIe lanes for high-performance graphics cards.
- Optimized for dense computing environments.
- Facilitates high-bandwidth data transfer to GPUs.
- Ensures robust physical and electrical connection for GPUs.
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Product Overview
This is a GPU Expansion Riser Board specifically designed for Dell PowerEdge C4130 servers. It facilitates the integration of multiple GPUs to enhance computational power for demanding workloads.
Technical Information
| Product Type | GPU Expansion Riser Board |
| Compatibility | Dell PowerEdge C4130 |
Additional Specifications
| Interface | PCIe |
Product Description
The Dell CN-0GHV6W GPU Expansion Riser Board is a critical component for the PowerEdge C4130 server, engineered to support the integration of powerful Graphics Processing Units (GPUs). This riser board is essential for configurations that require accelerated computing capabilities, such as machine learning, artificial intelligence, scientific simulations, and high-performance data analytics. It provides the necessary physical mounting and electrical connections to ensure stable and high-speed communication between the server's motherboard and the installed GPUs. Leveraging PCIe technology, this expansion board is designed to maximize bandwidth and minimize latency, allowing the GPUs to perform at their peak potential. The PowerEdge C4130 is built for dense computing, and the CN-0GHV6W riser board is a key enabler of this density by efficiently accommodating multiple GPU modules within the server chassis. Its design adheres to Dell's stringent quality and performance standards, ensuring reliability for mission-critical applications. Installation of the CN-0GHV6W riser board allows businesses to significantly boost their processing power without needing to replace the entire server infrastructure. It offers a scalable solution for organizations looking to enhance their computational resources for AI training, deep learning inference, or complex rendering tasks. The board's robust construction and precise engineering ensure long-term operational stability and performance.
