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03-10-2017 12:25 PM

5 Reasons to take load off CPU with a GPU

Some users who lease dedicated hosting servers for hosting online and video games search for ways to improve products so they would fit the requirements better. Pretty often, they request dedicated servers with quicker processors or GPUs to boost speed of their hosting service. Do GPU-driven servers can outperform CPU ones, and what are the main benefits you can reap from them?

What makes GPUs more preferable?

  1. 3D processing: GPUs are irreplaceable for 3D rendering. When it is performed by a CPU-only server, the processing is pretty slow because of linear request handling. If you turbo-charge your server with a GPU, performance will be significantly increased, because it may simultaneously process much more requests simultaneously. Since compute tasks are offloaded from the CPU, it may process some other sequential tasks.
  2. Speed Acceleration. It’s a widely acknowledged fact that GPUs boost speed, but how does it work? Being comprised of several cores, a GPU can handle hundreds of tasks simultaneously accelerating applications tenfold over usual CPU-only applications. Since CPU relies of cache to reduce latency of memory access, it requires a lot of space. GPU increases bandwidth with cache memory. While CPU waits for RAM to become available to execute a thread, a GPU will switch to another task that is ready for processing, which minimizes latency and contributes to better results.
  3. Number cruncher. Since GPU has state-of-art graphic cards with up to 2880 (!) cores, it possesses far better performance, when it comes to number crunching and graphics processing. A CPU supports only 1-2 thread in a core, while multiprocessors can execute more than thousand threads at once. That’s the reason why users specializing on mining cryptocurrencies select GPU instead of CPU. 
  4. Large data analytics. Those who need to make real-time data-driven decisions choose GPUs for data analytics. Shazam, Dell, Cisco and Gatorade are good examples: GPU help them to process more than 500 million requests daily. Besides, with GPU you get data delivered ten times faster than with a CPU-based system.
  5. VDI environment. GPU hardware acceleration can be shared between up to 32 users on virtual desktops. You can try NVIDIA GRID tool for improving graphics performance  can be shared between virtual desktops–up to 32 users can share a graphics board. It features multi-GPU design, and provides enough memory for processing data in graphics-intensive applications.

Although GPUs were traditionally used to process sophisticated algorithms and huge data sets for computer science applications and engineering tasks, now other companies discover alternative uses of GPUs, such as image recognition, audio and video search, analytics of bulky data. Therefore, GPU dedicated servers are becoming more and more demanded by heavy content producers and web design agencies that create heavy games, 3D videos, and interaction applications.

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