NVIDIA Tesla dedicated servers equipped with professional NVIDIA GPU cards are ideal option for AI, Deep Learning and HPC - configurable with up to 4x GPU's for massively paralell computing.
GPU passthrough allows to directly present an internal PCI GPU to virtual KVM machines. The GPU card is dedicated to the VM and cannot be used by other clients. GPU performance in virtual machines matches GPU performance in dedicated servers. Since we use large multi-card nodes for vGPU, virtual machines come at a cheaper price.
Looking for a non-standard OS? We have a wide selection of ISO images in our control panel. Or you can use your own image and install the OS via IPMI. All our servers are unmanaged. Administration services can be provided for a fee. Please contact us for any questions.
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Do you need a GPU server based on NVIDIA TESLA V100 / T4 / P100? Get a quote!
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TIER III Data Centers
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A replacement server is always available
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Our Services
We provide a free trial period for companies only.Specify your corporate address in the application form!
If you don't find the right configuration, you can always contact our Sales Department. Our managers will help you with your requirements. We are very flexible.
If you don't find the right configuration, you can always contact our Sales Department. Our managers will help you with your requirements. We are very flexible.
You can choose a suitable Data Center in the Netherlands and the USA
We use an individual approach with each client, which is reflected not only in our technological solutions but also in the appropriate Data Center. We offer Data Centers TIER III categories, which allows us to offer the most flexible solutions for the needs of every client.
For business-critical applications, availability is paramount. In this case, you need a certified Tier III category data center at a minimum. For minor tasks, TIER II or even TIER I Data Center will suffice.
A complete list of the Data Centers and their characteristics can be found here.
If availability is crucial to you, we recommend certified Data Centers, i.e. EuNetworks.
If you would like to test the Internet speed to resources hosted on our servers, you can make use of Speedtest or Looking Glass without having to wait for the deployment of the test server.
You can request a test server if you would like to:
test the compatibility of the software and the chosen configuration of the dedicated server or VPS with GPU cards;
make sure that the server configuration chosen is capable of all the tasks at hand and that server upgrade (RAM, HDD, etc.) won’t be necessary in the near future;
evaluate the performance of HOSTKEY’s servers in practice.
When providing a test server, HOSTKEY uses an individual approach to every client. On average, the trial period is 3 days.
If you would like to get further information regarding getting a test server and/or terms and conditions of the service, please contact our managers.
After the trial period is over, you can pay for the server and continue using it. If we haven’t received your payment within 3 days after the end of the trial period, the server will be terminated and all data deleted.
Note: HOSTKEY operates under the current legislation of the Russian Federation, the Netherlands and the United States of America.
Therefore, we ask you to use our servers without breaking the laws of the corresponding country.
Requirements for the use of servers in the corresponding country.
All our services are paid for in advance. We accept payments via credit card, PayPal, P2P cryptocurrency payments from any wallet, application or exchange through BitPay. We also accept WebMoney, Alipay and wire transfers. Read more about our payment terms and methods. Read more about payment terms and methods.
We are very confident in our products and services. We provide fast, reliable and comprehensive service and believe that you will be completely satisfied.
You can ask for a test server for 3-4 days for free.
Refund is only possible in case of an accident from our side with your server being offline for 24 hours or more due to that.
Read more about refund procedure.
Customers whose servers come with unlimited bandwidth are committed to a fair usage policy.
That means that servers on the 1 Gbps port cannot use more than 70% of the allocated bandwidth for more than 3 hours a day.
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With GPU accelerated server platforms, high-performance computing become a key to empowering progress in science and engineering. Equipped with Nvidia Tesla GPU, servers are capable of greatly boosting performance thanks to parallel computing power of graphical processing units.
In just a few minutes a GPU dedicated server that can host up to eight NVIDIA Tesla GPU accelerators can do jobs that take days or even weeks when a regular CPU server is used. What is more, if you compare GPU server cost with that of CPU, it is clear that for a great variety of tasks it will be reasonable to rent a GPU server rather than a conventional CPU-only one.
Hundreds of software applications have been already GPU-accelerated, and their number is growing rapidly.
No wonder that Nvidia Tesla certified servers are extensively employed in lots of spheres where heavy data streams are to be processed - artificial intelligence, training sophisticated deep learning networks, visualizing big data, virtual reality, augmented reality, to name a few.
Also, processing results of scientific research often requires parallel computing. Among the sciences that could greatly benefit from use of GPU servers are quantum chemistry and physics, geoscience and bioinformatics, climate and weather modeling, computational fluid dynamics, structural mechanics, and many more.
What is more, thanks to GPU-Accelerated Server Platforms from Nvidia, now it is possible to pick an ideal server for any workload, Nvidia offers classes of servers optimal for various applications: training, supercomputing, and inference (HGX-T, SCX, and HGX-I respectively). providing both scientists and businesspeople with highly efficient but affordable solutions.
Tesla cards are also widely applied in heterogeneous computing systems, which make the most of both CPUs and GPUs to achieve higher energy efficiency and lower cost.
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