lewis hamilton
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Apr 13, 2021
4:12 AM
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When you need the massive parallel processing power of GPU-accelerated computing, Thinkmate provides GPU dedicated server and workstation options that deliver superior reliability and expandability. Thinkmate GPU dedicated servers are available in a variety of form factors and offer breakthrough performance, excellent manageability and exceptional efficiency.
A GPU dedicated server hosting uses a hybrid computing model combining CPUs and GPUs to increase application performance. A GPU, or graphical processing unit, has a massively parallel architecture comprised of thousands of small processing cores that makes it uniquely suited to accelerating parallel calculations. Originally built for graphics processing, GPU servers are now indispensable for high-end CAD workstations as well as applications that involve compute-intensive tasks like rendering and finite element analysis. With a GPU dedicated server, you can offload these tasks to the GPU and enable the CPU to continue performing the serial processing tasks for which it is designed. Ultimately, a GPU dedicated server allows you to use a single machine to accomplish much more.
I hope this information is helpful. To know more about virtual dedicated server hosting or Windows 10 virtual desktop visit Apps4Rent.
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1 post
Aug 22, 2022
10:56 PM
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If your organization deals with 3D visualizations, machine learning (ML), artificial intelligence (AI), or heavy computing of some sort, how you perform GPU computation matters a lot.
Traditionally, deep learning models in organizations took an extensive amount of time for training and computation tasks. It used to kill their time, cost them a lot, and left them with storage and space issues, reducing productivity.
The new age GPUs are designed to solve this problem. They offer high efficiency to perform heavy computations and faster training for your AI models in parallel.
According to Indigo research, GPUs can offer 250 times faster performance than CPUs while training neural networks associated with deep learning.
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