PNY NVIDIA Tesla M10 32 GB GDDR5 - Graafikakaardid - Süsteemikomponendid - Computer Components - MT Shop
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PNY NVIDIA Tesla M10 32 GB GDDR5

Manufacturer: PNY Product Code: 229075084 EAN: 03536403351397 MPN: TCSM10M-PB
PNY NVIDIA Tesla M10, Tesla M10, 32 GB, GDDR5, 256 bit, PCI Express x16 3.0
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3 996.51 €
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Product Information


Information
Manufacturer PNY
Product code 229075084
EAN 03536403351397
Manufacturer part number TCSM10M-PB
Category Graafikakaardid

Product Description


GREAT USER EXPERIENCE. HIGH USER DENSITY

IT needs a software-defined approach to virtualization in the data center that delivers scalability, data security, and simplified manageability. However, adoption of desktop virtualization solutions has been limited by their failure to deliver a user experience that’sas good as physical devices.
The NVIDIA Tesla M10 GPU accelerator works with NVIDIA GRID™ software to provide the industry’s highest user density for virtualized desktops and applications. It supports 64 desktops per board and 128 desktops per server, giving your business the power to deliver great experiences to all of your employees at an affordable cost.

GRID technology helps you protect your most valuable data, keeping it secure in the data center while providing just the right level of access to users. Keep your corporate intellectual property safe while also boosting productivity across the enterprise. NVIDIA GRID has three different editions that let you assign the right level of resources to each of your users; Virtual PC, Virtual Workstation, and Virtual Workstation Extended. When you create a new desktop, you simply assign a license based on the user profile that will be accessing it. IT managers can easily assign the optimal amount of graphics memory and deliver a customized graphics profile to meet the specific needs of each user. Every virtual desktop has dedicated graphics memory, just like they would at their desk, so they always have the resources they need to launch and run their applications. GRID enables up to sixteen users to share each physical GPU, so the graphics resources of the available GPUs can be assigned to virtual machines in a balanced way.

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