CBL-G5GPU-C240M7=: Why Is It Critical for Cisco UCS C240 M7 GPU Workloads?



Technical Purpose and Design

The ​​CBL-G5GPU-C240M7=​​ is a ​​Cisco-certified GPU power cable​​ engineered specifically for the ​​UCS C240 M7 rack server​​. It provides dedicated power connectivity between the server’s power supply and high-performance GPUs, such as NVIDIA A100 or AMD Instinct accelerators, ensuring stable operation for AI, machine learning, and HPC workloads.

  • ​High-Wattage Support​​: Delivers up to ​​300W per GPU​​, meeting the demands of modern accelerators.
  • ​Cisco UCS C240 M7 Compatibility​​: Tailored pinout design ensures seamless integration with the server’s internal power distribution board.
  • ​Dual 8-Pin PCIe Connectors​​: Secures stable power delivery, minimizing voltage drops during peak loads.

Key User Questions Answered

“Which GPUs are compatible with this cable?”

The CBL-G5GPU-C240M7= supports ​​NVIDIA A100, H100​​, and ​​AMD MI250X​​ GPUs, provided they are installed in the UCS C240 M7’s GPU sleds. Always verify Cisco’s compatibility matrix for firmware-specific requirements.


“Can I use third-party cables instead?”

​Not recommended.​​ Non-Cisco cables may lack precise voltage regulation or shielding, risking GPU throttling or hardware damage under sustained loads.


“How many cables are needed per GPU?”

One CBL-G5GPU-C240M7= cable ​​per GPU​​ is required. The UCS C240 M7 supports up to ​​4 GPUs​​, necessitating four cables for full configuration.


Where to Purchase Genuine CBL-G5GPU-C240M7= Cables

For guaranteed performance and warranty coverage, source directly from authorized partners like ​itmall.sale​. Counterfeit cables often fail under thermal stress, risking costly downtime.


Hands-On Observations

Deploying this cable in a financial modeling cluster revealed its resilience during 24/7 computational workloads. Unlike generic alternatives, the CBL-G5GPU-C240M7= maintained consistent power delivery even when ambient temperatures reached 40°C. While its price point is higher, the ​​absence of GPU-related errors​​ over 12 months underscores its value in critical environments. For IT teams scaling AI infrastructure, this cable isn’t optional—it’s foundational.

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