The web hosting industry is full of the bigger, faster, now mentality. Many of our clients want data pushed to the max, and we don’t blame them one bit! Luckily, technologies are constantly improving to help us reach our ever-increasing expectations.
For example, clients often ask about the possible benefit of adding a Graphics Processing Unit (GPU) to their hosting solution in an effort to accelerate their hosting capabilities. Adding GPUs can multiply performance due to their ability to compute and process large amounts of data while leaving the CPU free to process tasks. However, a GPU isn’t always the best option for all hosting platforms.
Today we take a more detailed look at exactly what GPUs are, how they work to increase data processing speeds, and who should consider adding a GPU to their web hosting solution.
What are GPUs?
Graphics Processing Units are a specific type of processor that was originally designed to be used on a graphics card. GPUs help computer graphics quickly appear on a screen. However, GPUs that are used for reasons besides computer screen graphics are called General Purpose GPUs (GPGPU).
GPUs differ from modern CPUs due to their higher numbers of cores on each chip. GPUs can perform many basic computing tasks at the same time. A CPU may get bogged down in the bulk. Simultaneous computing tasks work well for a variety of industries beyond the ability to calculate hundreds of thousands of polygons at the exact shade necessary as in computer screen graphics.
How do GPUs work?
GPUs are made from multiple cores and designed to simultaneously handle hundreds of tasks, also called threads. By working many threads at the same time, GPUs accelerate speeds up to tenfold. CPUs are consistently waiting for cache memory to complete tasks, whereas GPUs can simply switch to another thread that is free for processing. This process reduces latency and delivers results much faster. By adding a GPU to your web hosting solution, you can amplify processing power, cut latency, and improve speeds.
Who should consider adding GPUs to their solution?
GPUs aren’t exactly a one-size-fits-all solution. However, there are situations where a GPU is perfectly suited. Currently, there are over 550 various purposes designated for GPUs. From climate monitoring to cryptocurrency mining, there is a definite need for increased computational power.
This ability to perform functions a CPU would struggle with explains why GPUs have outgrown their original role of rendering three-dimensional graphics for Millennial computer games. Today, GPU tasks are specifically designed to play to the strengths of these multicore microprocessor chips. Below are five examples of situations in which a GPU might be more suitable than a CPU…
1. Graphics processing.
It would be a mistake to overlook arguably the most significant of GPU tasks. Although a graphical processor’s clock speed is lower than that of a CPU, the presence of numerous cores and the ability to focus on a single task (to the exclusion of all others) makes it ideal for rendering polygons and fractals. Indeed, computers without graphics cards often struggle to perform visual functions more basic than outputting two-dimensional graphics onto a screen.
2. Bitcoin mining.
Again, no great breadth of talent is required to perform repetitive mathematical calculations before they’re uploaded to the blockchain. This is the core service performed by bitcoin miners, who are paid with cryptocurrency fragments in exchange for solving elements of complex math problems. This is one of the leading GPU tasks, with huge arrays of processors yoked together to maximize revenue.
3. Machine learning.
Many modern internet services rely on algorithmic analysis, parsing huge volumes of data to establish optimal outcomes. GPUs are great for tasks like identifying fraudulent ecommerce transactions or determining what information someone using a virtual assistant might be searching for. Brute force processing is often the best way to wade through oceans of raw data before reaching a definitive (and hopefully accurate) outcome.
4. Video acceleration.
Building on their original purpose of graphical output, GPU tasks have expanded to cover video acceleration and transcoding. The latter describes the process of converting a video file from one format into another. It has become crucial in the fiercely contested world of streaming media. However, transcoding involves extensive processing power, which is where the multi-core design of GPUs comes into its own.
5. Scientific computing.
Scientists are rarely slow to spot potential, and the lightning-fast calculations offered by GPU chips have led to their adoption across numerous scientific environments. Notable examples include astrophysics, molecular modeling and weather forecasting. GPUs role in climate research has underpinned some of the environmental data behind today’s growing awareness of climate change.