EN-Labs 11-001-366 PCIe x4 USB 3.2 10Gbps 5-port card
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- 12CM Case fan,screw…
HPE
Accelerates deep learning and HPC workloads with 32 GB HBM2 memory and thousands of CUDA cores
The HP V100 is a compute-focused graphics card built on the NVIDIA V100 GPU with 32 GB of HBM2 memory. It targets data-centre workloads such as deep learning training, high-performance computing simulations and scientific visualisation. Thousands of CUDA cores divide large tasks into concurrent threads for faster results. This card is designed for integration with select HPE ProLiant server families.
Traditional CPU platforms can no longer keep pace with growing computational and graphics demands from complex models. The V100 delivers dramatically higher application acceleration for deep learning, scientific and commercial workloads. The jump is worth it when simulation turnaround or graphics fidelity for demanding 3D models becomes a bottleneck. Buyers who need only basic display output or light inference should look elsewhere.
The 32 GB HBM2 frame buffer sets a hard ceiling on model size and batch dimensions that can reside in GPU memory. Workloads exceeding this capacity must spill to system memory, reducing throughput. Deployment is restricted to qualified HPE ProLiant server configurations; the card cannot be used in standard desktop chassis or non-certified platforms. Power and thermal budgets must also align with the target server specification.
| Brand | HPE |
|---|---|
| Chipset Manufacturer | NVIDIA |
| GPU | V100 |
| Memory Type | HBM2 |
The V100 FHHL model is a full-height half-length card designed for standard PCIe slots in HPE ProLiant servers.
The card requires auxiliary PCIe power cables from the server PSU; forgetting to seat both connectors is the most common error.
HBM2 memory is soldered to the GPU package, so the entire accelerator is replaced if memory errors appear in diagnostic logs.
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