Modern computing is going faster than ever. Tech companies now have to deal with unprecedented information.
Computers must be absolute workhorses if we want to keep the business flowing. While the concept of GPU is nothing new, we have noticed a sharp increase in GPU-dedicated servers.
While CPUs are still the brain of a computer, their performances might not be enough to sustain a whole float of computers rendering detailed graphics and operating multiple tasks at once.
Regarding this, using GPUs as dedicated servers is a small revolution in computing because it resolves at least three important issues: cost-efficiency, accelerated processing, and enhanced graphics.
This evolution can only mean that computers can process tasks faster and should cost less to operate. A GPU dedicated server works closely with CPUs to run everything smoothly, minimizing latency.
They are great for various industries, ranging from scientific organizations, institutions that require a lot of data, and crypto-mining.
Difference Between CPU And GPU
There was a time when the CPU (Central Processing Unit) was the brain of the operation.
Computers were slow enough to work independently and didn’t need to perform many tasks simultaneously. Nowadays, servers need to operate many tasks in a very short time.
CPUs are still the most important link in the computer ecosystem. However, they cannot process many tasks for themselves, and they gladly accept the help of GPUs, which can be described as a massive architecture of graphics cards in the center of a server.
Here’s an analogy that you might find helpful. Suppose the CPU is like the main chef of a big restaurant. The chef can cook delicious dinners on a small scale.
GPUs are like line cooks that can cut onions, stir the sauce, and repeat operations that a CPU could only do with time.
Integrating a GPU dedicated server has become mandatory in industries requiring fast processing.
Of course, buying and operating a float of graphic cards represents a very high cost for a company.
However, this cost can be mitigated due to the three main benefits of owning a GPU-dedicated server.
First Benefit: Faster Parallel Processing
Like the famous Daft Punk song, GPU servers process things harder, better, stronger, and faster than CPU servers.
This is mainly because CPUs are made for sequential processing, which implies that they can only do a certain amount of tasks during a short amount of time.
GPUs, on the other hand, function with parallel processing. That means they can process thousands of mathematical tasks simultaneously.
The benefits of this rapidity are rather obvious. For industries that require a significant amount of daily tasks, GPU servers can tackle very complex things ranging from deep learning to simulation and data analysis.
Remember, your server’s CPU is still your organization’s main chef, but GPU-dedicated servers can help it tremendously by accomplishing tasks that the CPU could do in a longer time.
A GPU-dedicated server needs a pretty big stack of graphic cards to operate. It could go up to hundreds of graphic cards, depending on the sheer size of the computing architecture.
Graphic cards vary in quality and power. The bigger names on the market are the GEFORCE RTX or NVIDIA cards. A company can determine its need for graphic cards by asking for a quotation.
Second Benefit: Enhanced Graphics and Visualization
Point of view: You’re part of a company that shoots, edits, and publishes videos daily for many clients. These tasks are very demanding, and they need to be performed quickly.
You have about 30 employees that work non-stop on projects. Your employees won’t be satisfied if tasks take forever, and you will fall behind deadlines if you don’t have a responsive architecture.
Most video editing needs powerful computers. It consists mainly of repeating the same kind of tasks every day.
Graphic cards are improving each year, and you will always find a model that will surpass the competition in its framerate, latency, and accuracy.
Once again, the main perk of a GPU-dedicated server is to relieve the CPU from doing menial tasks repeatedly so it can focus on the most important stuff.
This is called off-loading the CPU, and it will accelerate every process you’re involved with on a day-to-day basis.
Rendering a video in 4K could take days if done by your main CPU. With an army of graphic cards, it will take only a few minutes.
This list of benefits is almost endless, and it has positive effects on many areas of computing, especially with new technologies related to artificial intelligence.
Third Benefit: Energy Efficiency and Cost Savings
News Flash: Companies are here to make money, and organizations such as hospitals and big offices can’t afford to get behind for an hour or two.
We want GPU-dedicated servers to be fast and efficient, but it’s even better if such an installation can save money and energy.
Computer engineers have noticed that switching to a GPU-dedicated server is more cost-efficient than relying on the CPU for repetitive tasks. Firstly, all GPUs can perform enormous tasks by parallel processing, saving considerable time.
Moreover, graphic cards are getting more and more self-sufficient. This results in energy savings that can relieve your companies of expenses, such as electricity.
According to Hivelocity, one GPU server can handle the same tasks as 400 CPU servers. Of course, there are specific cases where this number can go up or down.
The main idea is that gearing up with GPU-dedicated servers will serve your company in the long run and help make savings after several months of use.
The environmental aspect of a GPU-dedicated server cannot be neglected. Everywhere in the world, some data centers produce a lot of heat and require a gigantic amount of electricity to operate.
This has a significant impact on the planet, and it’s up to computer engineering to find solutions to fight against climate change.
Middle-size companies and organizations can also be leaders in cost-effective and environmentally friendly processes.
In this regard, it’s important to get equipped with the latest technology of GPU servers to mitigate the devastating effects of climate change and ultimately save money.
