Deep learning is pushing the limits of enterprise computing. As a subfield of machine learning, its goal is to imitate the structure and function of the brain in how it solves problems. This task requires creating artificial neural networks, which need to learn to improve their ability to make decisions. Gathering enough data to run deep learning algorithms takes enormous amounts of processing power. And, most organizations can’t afford to increase their infrastructure indefinitely.

How can businesses use compute resources more efficiently to keep up with the needs of deep learning? One way is by leveraging CPU virtualization. CPU virtualization is the act of turning physical hardware into a digital asset that can be accessed from anywhere. Let’s look at how CPU virtualization helps teams share IT infrastructure.  

CPU Virtualization Helps Share Resources Efficiently

Most organizations with on-premise infrastructure allocate resources evenly. This can create bottlenecks when one team has bigger workloads than the rest. Imagine that you have significant computing infrastructure and have allocated 10 physical processors to 10 different teams. It’s unlikely that all 10 teams will be using all of their compute resources at the same time. But, because your resources are allocated physically and can’t be easily shared, unused resources are wasted. The inability to share resources and/or monitor performance far outweighs the gains of a dedicated CPU. How does CPU virtualization fix this?

CPU virtualization takes all of your processors and adds them to a virtual pool. This means that potentially all of the compute resources could be allocated to a single team when unused by other teams. For example, if one team is running a complex ML algorithm, they can have access to 50-60% of the computing resources instead of being limited to the 10% that’s allocated to them physically. The performance gains would help speed up deep learning algorithms, freeing up hardware for the next task.

CPU virtualization improves monitoring and optimization

Graph of CPU performance across the company

When looking at the example above, it brings another advantage of virtualization to the fore. Computing capabilities need to match the way people work. It’s unlikely that every team will need a constant 10% of the compute resources. It’s more likely that teams will fluctuate from not needing much to needing as much processing power as they can get. Flexible compute resources allow you to adapt to current needs and shift resources at will.

Monitoring how teams use computing resources is another major advantage of virtualization. Collecting usage data with standard computing is a chore because it has to be done separately and then aggregated and analyzed to extract insights. CPU virtualization pools your resources and can be used in conjunction with software that helps easily decipher where resources are going.

Understanding how computing resources are being used is invaluable when planning future infrastructure upgrades. Teams can then truly grasp if they are operating at their infrastructure’s capacity, and if so, which projects are using the most resources. It’s then possible to ensure the most resource-intensive projects are adding value that is commensurate with their cost. This understanding is key to allocating budget to projects that add real value to your business.

So far, we’ve seen how CPU virtualization can help:

  • Share compute resources between teams efficiently
  • Provide better monitoring of CPU utilization
  • Give teams on-demand control of computing infrastructure

These benefits don’t mean that teams should skip hardware upgrades or that component choices don’t matter.

The Right Computing Components Can Improve Virtualization Performance

Businesses can optimize their computing resources by choosing components that are designed for superior performance during virtualization. Superior CPU virtualization will allow you to run applications in a VM as if they are running natively on a dedicated CPU.

We help our clients build custom hardware that matches their CPU virtualization needs. And that’s just the beginning. Whether you need GPU, memory, or I/O virtualization, we can help you design hardware for your use case. If you’re looking to make infrastructure improvements but don’t want the supply chain headache, talk to one of our experts today.

Intequus Cloud Education


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