Memory
| Graphics adapter memory type |
GDDR5 |
| Memory bandwidth (max) |
208 GB/s |
| Memory bus |
320 bit |
| Discrete graphics adapter memory |
5 GB |
Performance
| DirectX version |
11 |
| OpenGL version |
4.3 |
| Shader model version |
5.0 |
| PhysX |
N |
| TV tuner integrated |
N |
System requirements
| Linux operating systems supported |
Y |
| Windows operating systems supported |
Y |
Processor
| Graphics processor family |
NVIDIA |
| CUDA |
Y |
Power
| Power consumption (typical) |
225 W |
Ports & interfaces
| Interface type |
PCI Express 2.0 |
Weight & dimensions
| Depth |
110 mm |
| Width |
265 mm |
Additionally
| Graphics controller |
Tesla K20 |
| Dual-link DVI |
N |
Nvidia Tesla K20 5GB GDDR5, PCI Express 2.0 x16
The NVIDIA Tesla Computing Modules seamlessly integrate GPU computing with HP ProLiant servers for scale-out deployments. The Tesla GPUs have a capacity of up to 6 GB of GDDR5 memory with ECC, and peak performance of up to 1.32 double-precision Tflops and up to 3.95 single-precision Tflops. The Tesla K20 and K20X GPU Modules are single double-width PCIe modules based on the NVIDIA Kepler architecture. The Tesla K10 Dual GPU Module is a single PCIe module with two GPUs that are optimized for single-precision performance. Each GPU has 4 GB of memory and a peak performance of 2.29 single-precision Tflop. The Tesla M2070Q combines Tesla’s high performance computation with the NVIDIA Quadro® professional-class visualization in the same GPU.
Delivering Increased Performance to Solve Problems in Minutes Instead of Hours.
The NVIDIA Tesla Computing Modules seamlessly integrate GPU computing with HP ProLiant Server series for scale-out deployments. Computational time can be dramatically reduced for parallel applications, offering quicker time to solutions. As parallel processors, GPUs excel at tackling large amounts of similar data because the problem can be split into hundreds or thousands of pieces and calculated simultaneously. The combination of GPU processors – delivering high performance per watt - and HP ProLiant servers – the industry’s most power-efficient computers – dramatically reduces the carbon footprint required for timely solutions. Includes the CUDA programming interface and third-party CUDA development tools, as well as the HP Cluster Management Utility (CMU). CMU will monitor and display GPU health such as temperature, and will also install and provision the GPU drivers and the CUDA software.
