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Cloud GPU: The Benefits of Using GPUs in the Cloud

4 Mins read
Cloud GPU

If you’re considering cloud computing and want to know if a Graphics Processing Unit (GPU) is necessary, allow us to explain the advantages of using cloud-based GPUs for data-intensive applications.

What is a GPU?

Computers are powerful machines that rely on their heart or the core – the central processing unit (CPU). This component is an essential part of a computer, enabling fast mathematical and logical operations as well as controlling software execution, input/output devices, and a range of other resources.

CPUs operate in a specific way. While capable of providing efficient solutions for many applications, CPUs struggle when required to handle high-throughput calculations in parallel. This challenge is especially evident for applications involving graphical processing such as video gaming or digital art production.

This is where a graphics processing unit came in.

A GPU is a specialized type of processor that is designed specifically to handle the complex calculations required to render images and video. GPUs are an essential component of many modern computers, particularly those used for gaming, video editing, and other graphics-intensive tasks.

The primary function of a GPU is to process and display images and video, but they can also be used to perform other types of calculations. For example, many modern GPUs are powerful enough to be used for scientific and mathematical applications, such as simulations, data analysis, and machine learning.

GPUs are different from traditional processors, such as CPUs, in that they are designed to perform many calculations simultaneously, rather than sequentially. This makes them well-suited for tasks that require a lot of parallel processing, such as rendering images and video. Many modern GPUs have hundreds or even thousands of processor cores, which allow them to handle complex tasks much faster than a traditional CPU.

What do cloud platforms do?

Before we learn about the benefits of using GPUs in the cloud, we need to observe the kinds of applications cloud platforms include.

  • Data Storage: Cloud computing provides online space to store data, such as documents, audio, videos, and images. Users can store huge volumes of data in cloud storage and access it over multiple devices.
  • Analytics: The gargantuan amount of data is beyond the scope of traditional storage systems. Thankfully, cloud computing provides limitless capacity to store and explore large volumes of big data, allowing its users to unlock invaluable business intelligence.
  • Machine Learning: Machine learning algorithms can autonomously explore vast amounts of data to uncover insightful strategies and solutions. By repetitively working through their models in parallel processing, these advanced systems can continuously refine themselves for optimal performance.
  • Pattern Recognition: From machine learning to analytics, pattern recognition can be seen at every level of cloud processing. But recently more complex pattern recognition tasks such as biometric identification, facial recognition, etc., using behavioral identifiers have become a standard in business applications.

What GPUs in cloud platforms do?

Now, let us connect GPU with cloud computing. In the last few years, cloud GPUs have become the basis of high-performance cloud computing to meet the ever-increasing demand for pattern and analytics-based workloads. Companies are advised to use Cloud GPUs by ZNetLive for light to heavy computations.

Let us understand the benefits of using Cloud GPUs:

Local Resources Usage Reduction: Cloud computing essentially provides limitless access to powerful resources without consuming local resources. Complex Machine Learning models and rendering tasks can interfere with the everyday use of computers, leading to sluggish performance or even reduced functionality. Outsourcing to the cloud eliminates computing stress and provides users with a hassle-free experience on their devices.

The traditional role of the personal computer has changed. With the advent of cloud computing, the computer has become a command center. It orchestrates complex computational tasks without requiring direct processing efforts by itself.

Rapid and Easy Scaling: ZNetLive NVIDIA GPU cloud provides easy scalability and is powered by world-class infra by NVIDIA. Thus, you get seamless scalability, allowing you to expand your team or workload quickly and easily.

Time Saving: Over the past ten years, computers and Kanban product management systems have demonstrated the importance of iterative work. For designers, this is especially applicable; shorter rendering times can lead to faster iteration – going from a delay of 8 minutes down to 10 seconds makes an immense difference that allows creators an unparalleled level of fluidity in their workflow.

By using a small render farm, an experienced team can drastically decrease their render times from days to just a few minutes. Not only will this lead the team workflow towards far more efficient outcomes but will also sustain it for years. Setting up a small render farm may take anything from hours to one week, depending upon experience.

Cloud GPUs can help you adjust the modelling process of machine learning from anywhere between 8-12 hours to a mere 10-15 minutes.

Cost Reduction: GPUs offer unparalleled power efficiency and workload streamlining capabilities, allowing businesses to benefit from lower hardware costs while avoiding wasted resources. Additionally, once the system is up-and-running, minimal management of its infrastructure will be required meaning less overhead expenditure for companies looking to leverage this technology.

Utilize GPU-Driven Cloud Systems from ZNetLive

Technology advancement has pushed the boundaries of distributed cloud processing, demanding solutions for more complex problems. For this, optimized hardware is needed to process copious amounts of data daily. A combination of advanced GPU-powered hardware is necessary to maintain high throughput levels while accommodating scalability needs associated with data-intensive tasks like machine learning and genomic sequencing, and managing big data sets efficiently.

To get this robust infrastructure, start with Cloud GPU now. You’ll get a comprehensive list of features, including cloud storage options, powerful functions supporting efficient database management, and seamless integration with frontend applications.

To learn more about ZNetLive’s Cloud GPU, contact our team today!

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About author
Priyanka Dadhich – a content writer, can usually be found reading books. She likes to write about technology, healthcare, travel and fashion. Priyanka loves coffee and listens to music in her free time. She spends her free time with her family.
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