Don’t Let Headroom Dictate Your Budget
From the early days of digital technology, one of the most important parameters for a given engineering task was a measure of maximum capacity often referred to as “headroom.”
For example, when deploying a fleet of desktop computers for a team you would consider the maximum processing power and memory the users might need, even if for just a few moments every now and then. Most of the time, a user probably wouldn’t use more than 20% of a computer’s resources, but it was important to have that extra headroom just in case.
When the technology is comparatively inexpensive, that approach makes sense. But when you apply that kind of thinking to hardware requiring a high capital expenditure—such as the graphic processing units (GPUs) critical for applications such as autonomous driving, edge medical applications, machine learning, and artificial intelligence—it can overwhelm an organization’s budget.
How Virtualization Reduces Hardware Costs
Virtualizing graphics processing units (GPUs) and central processing units (CPUs) in a rack reduces hardware costs in two ways: you can buy less of it and use what you already have more efficiently.
Virtualization allows users to take advantage of the fact that GPUs and CPUs rarely operate anywhere near capacity. Virtualization abstracts the hardware layer from the software layer, so a specific element of hardware doesn’t need to be tied to a specific application. Your hardware can then simultaneously operate multiple software applications.
Another key advantage is that virtualization allows portability from the application side. Instead of being tied to the physical hardware, the application is tied to a hypervisor (also known as a VMM or virtual machine monitor).
The hypervisor acts as a moderator, shifting applications to available space on the hardware, and allowing you to easily add new hardware, move existing hardware around, move applications to different hardware environments to improve efficiency, and make similar changes transparently.
With a hypervisor’s flexibility, an organization can install the new hardware, migrate the application to the new hardware, and retire the old hardware without as much downtime or having to perform any reconfiguration to the software. And because applications can easily be moved to different hardware, your services can recover from the failure of any single piece of equipment almost immediately
Get Expert Help With CPU/GPU Virtualization
Our engineering team has extensive experience with helping organizations explore the opportunities and benefits. We use specialized software that accesses logs from the current environment to analyze the resources that are being used and what needs to be in place to support an efficient virtual environment.
In addition, although virtualization can significantly reduce capital expenditures, the decision process must also examine all engineering aspects. Our engineering team brings the knowledge and practical expertise to help your organization make decisions about virtualization with greater confidence, and we work collaboratively with you to design a long-term infrastructure strategy.
For more information on virtualization, see our whitepaper, How CPU & GPU Virtualization Optimizes Hardware Performance.
Intequus is the only turnkey edge infrastructure provider with 30 years of custom hardware engineering experience. Our global logistics, continuous program management, and unparalleled lifecycle support simplify scaled hardware initiatives and ensure fast, reliable service for your users. By handling every stage of your edge hardware needs, Intequus ensures that you can stay focused on your business and your customers.
For more information, email us at email@example.com or call 1(800) 641-1475.