Save Big: Up To 10% Off On Multiple GPU Servers!

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Tesla K40 GPU Dedicated Server, Hosted GPU Dedicated Hosting

Resolve all your most needing High-Performance Computing (HPC) tasks with the help of Tesla K40 hosting servers. As per the NVIDIA Kepler™, Tesla GPUs are specially developed to deliver quicker, more productive computing performance.

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GPU Features in Tesla
K40 Dedicated Server

Developed on the compute architecture of NVIDIA Kepler™ and powered by CUDA, this is the best dedicated GPU server hosting for record stimulation and compute performance mainly for big data applications.

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L1 and L2 Caches

Utilize this GPU server to boost necessary algorithms like physics solvers, real-time ray tracing, and sparse complex multiplication where addresses of data are not known earlier.

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Asynchronous Transfer with Dual DMA Engines

Supercharges the performance of the system by transferring all crucial data over the PCIe bus while the computing cores are scraping other necessary data.

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GPU Boost

Our Tesla K40 GPU dedicated server allows all the operators to easily change power headroom to different kinds of clocks and get even more acceleration for carrying out different HPC workloads.

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Memory Error Protection

The GPU card in the case of a server easily meets a very important requirement, especially for computing efficiency and scalability in data centers. Both memories are equally ECC protected.

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Dynamic Parallelism

Allow GPU threads to produce new threads automatically. By simply making adjustments to the data without going to the GPU again, this significantly streamlines parallel programming.

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System Monitoring

Unite the GPU subsystem with the monitoring and management potentials of the host system, such as OEM or IPMI tools. GPU processors in the computing system are managed by the IT team.

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Hyper-Q

Enables various CPU cores to synchronically utilize the CUDA cores on specific or numerous Kepler-based GPU servers. This increases GPU usage, and reduces CPU computing times.

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Reliable Programming Environment with Programming Language

With this GPU server, customers have full freedom to utilize OpenACC and CUDA toolkits, especially for C and C++, to accelerate application parallelism.

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What Can Be Easily Run on Tesla K40 GPU Servers?

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Substitues of the dedicated server with Tesla K40 GPU

The best GPU server hosting to choose from to meet your daily work needs.

Frequently Asked Questions

This server is a modern GPU that is specially designed for driving complex computing, AI/ML, and scientific simulations. It provides optimal computational power and extended memory capacity for all tasks related to parallel processing.

This server has high computing power, 2,880 CUDA cores, and 12 GB of GDDR5 memory, making it an appropriate choice for all demanding computational workloads.

This server is used mainly for all high-performance computing (HPC) tasks, complex simulations as well as data analytics. It boosts various tasks like deep learning, climate prediction, and financial planning.

As compared to some other GPUs, the hosted Tesla server provides thousands of CUDA cores and vast amounts of memory, making it specifically compelling for applications needing high computational power.

Applications in the case of scientific simulations, artificial intelligence, and data analytics get a very good advantage from the capabilities of the server, including several fields like computational fluid dynamics, weather forecasting, and genomics.

This server is not designed for the purpose of gaming. It is developed for carrying out complex computational tasks instead of 3D graphical rendering, making it a lot more appropriate for scientific tasks.

The latest GPUs with innovative components and higher performance have been released, but the Tesla K40 is still suitable for various applications requiring its powerful computational power, even though it is very less useful as compared to the latest models.

Installation involves physically arranging the GPU on a united server, installing the authorized drivers, and configuring software to use the GPU server, especially for complex computation tasks. Follow all the guidelines that are provided by NVIDIA.