5 Reasons to Offload Your CPU With a GPU

5 Reasons to Offload Your CPU With a GPU

Lease web now provides chosen high-performance GPU servers in an attempt to broaden our product range and better fulfill the needs of our clients. Before I go into the specs, let’s have a look at the top five ways a GPU may help you. I am always in contact with our customers to see how we can enhance our products to better meet their requirements. Customers often want faster CPUs or even GPUs to accelerate their hosting platform.

What Gives GPUs an Advantage Over CPUs?

3D Rendering

GPUs were developed specifically for 3D rendering. Processing is sluggish when allocated to a CPU-only application owing to linear request handling. Inserting a GPU into your server improves performance many times over since they process and compute huge blocks of data at the same time. The CPU is free to perform sequential tasks now that the repetitive computing jobs have been offloaded.

Accelerating Speed

We’ve all heard that GPUs increase speed, but what exactly makes them function faster? A GPU, which is made up of many cores, is designed to handle hundreds of threads at the same time, tenfold faster than a CPU-only program. Cache is used by CPUs to decrease memory access latency, although it consumes a lot of chip area. With cache memory, a GPU increases its bandwidth. Whereas a CPU would wait for RAM to become available before processing a thread, a GPU will switch to another thread that is ready to process, lowering latency and providing quicker results.

Number Cruncher

A GPU can make a high-end CPU seem like a Commodore 64 when it comes to number crunching and graphics processing (involving millions of computations per second). This is due to the large number of cores found in GPUs–high-end graphics cards may have up to 2880 cores. A CPU can handle up to two threads per core. A NVIDIA CUDA core’s multiprocessor, on the other hand, can run an astounding 1024 threads. This is also one of the reasons why mining cryptocurrencies (Bitcoin, Lite coin, and so on) produces quicker results when a GPU is utilized rather than a CPU. Although, when it comes to mining cryptocurrencies, ASICS processors currently outperform GPUs.

Big data analytics:

GPUs are increasingly being utilized for big data analytics in order to make better real-time business choices. Shazam, which has a library of over 27 million songs, utilizes GPUs to identify a song from a sound sample recorded by its smartphone users. When compared to a CPU-based solution, real-time insights are provided 10 minutes quicker.

VDI environment

GPU hardware acceleration may be shared across virtual desktops in a VDI environment–up to 32 users can share a graphics card. NVIDIA GRID is a powerful technology for delivering better graphics performance when many users share a GPU. The optimized multi-GPU architecture with enough RAM and low-latency remote display increases user density for graphics-intensive applications.

GPUs are a better match for a variety of businesses.

Traditionally, GPUs have been employed to handle complicated algorithms and large data sets for engineering and computer science applications. Companies are increasingly investigating new applications for GPUs, such as voice search, picture recognition, and big data analytics.

In our Lease web GPU servers, we utilize NVIDIA Quadro 4000 and 6000 GPUs for clients in data mining and numerical analysis; heavy content producers such as advertising firms; and web design companies creating interactive apps, games, and 3D content.

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