Intel Arc Pro B70 32GB GDDR6 256-bit PCIe 5.0 x16 33P01IB0BB workstation graphics card
- PCIe 5.0 x16
- Intel
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Workstation GPU with 448 stream processors and 6GB GDDR5 on a 384-bit bus for compute and visualisation
The HP Tesla M2075 is a workstation graphics card built for high-performance computation in professional environments. It targets users running large, complex computational models on supported Linux platforms. The card delivers double-precision performance of 655 Gflops and over 1.3 single-precision Tflops. It integrates with the CUDA programming interface for GPU-accelerated workloads.
This plug-in card connects via a PCI Express 2.0 x16 interface for deployment in compatible HP ProLiant servers. The 384-bit memory interface supports 6GB of GDDR5 memory with ECC for data integrity. It is designed for scale-out deployments within the HP GPU ecosystem. Buyers needing a different interface standard or a card without ECC memory should consider other options.
The GPU features 448 stream processors to handle parallel processing tasks efficiently. HP Cluster Management Utility monitors GPU health metrics such as temperature and manages driver provisioning. The HP HPC Linux Value Pack includes GPU-aware job scheduling through Platform LSF. This configuration serves compute clusters rather than general-purpose graphics or gaming workloads.
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| Product | |
|---|---|
| Brand name | HP |
| Model name | A0R41A |
| Memory | |
| Type of memory | GDDR5 |
| Graphics | |
| Graphics processor | Tesla M2075 |
| Memory capacity | 6 GB |
| Shader units | 448 |
| Chipset maker | NVIDIA |
| Memory bus width | 384-bit |
| Ports & slots | |
| Interface type | PCI Express 2.0 x16 |
| Size & build | |
| Form factor | Plug-in |
| Shipping weight | 0.41 kg |
| Package size | 25 × 25 × 25 mm |
| Compatibility | |
| Supported operating systems | Linux |
The PCI Express 2.0 x16 interface delivers up to 8 GB/s of bidirectional bandwidth for the Tesla M2075.
The card uses a full-height PCI Express 2.0 x16 slot and occupies two adjacent expansion brackets.
Seat the card firmly in the x16 slot, secure the bracket screw, then install the NVIDIA driver and CUDA toolkit before workload deployment.
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