HPE Tesla M1060 2-slot Passive Module
- Brand: HPE
- Category:
- SKU: SH409A
- EAN: 0884962920954 8849629209546
HP Tesla M1060 2-slot Passive Module
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Description
The NVIDIA Tesla Computing Modules enable seamless integration of 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 655 double-precision Gflops or over 1.3 single-precision Tflop.
The Tesla M2070Q combines Tesla’s high performance computation with the NVIDIA Quadro® professional-class visualization in the same GPU.
The HP GPU Ecosystem includes the CUDA programming interface and third-party CUDA development tools, as well as HP-supported GPU-aware cluster software such 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. In addition, HP HPC Linux Value Pack includes a GPU-enhanced version of Platform LSF, with the capability of scheduling jobs based on GPU requirements.
The Industry’s Fastest Multi-core Processors, Integrated into HP ProLiant Servers
• May dramatically reduce computational time for parallel applications. Reduces time to solution, thus enabling businesses to solve problems previously limited by CPU speed
The Tesla M2070Q combines Tesla’s high performance computation with the NVIDIA Quadro® professional-class visualization in the same GPU.
The HP GPU Ecosystem includes the CUDA programming interface and third-party CUDA development tools, as well as HP-supported GPU-aware cluster software such 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. In addition, HP HPC Linux Value Pack includes a GPU-enhanced version of Platform LSF, with the capability of scheduling jobs based on GPU requirements.
The Industry’s Fastest Multi-core Processors, Integrated into HP ProLiant Servers
• May dramatically reduce computational time for parallel applications. Reduces time to solution, thus enabling businesses to solve problems previously limited by CPU speed