ColocationPLUS™ is proud to offer GPU server hosting. Our data centers are outfitted with the requisite cooling and power infrastructure to be able to support these high performance servers. Need help migrating your applications and data to a GPU based server? No problem! Our expert staff are standing by to get you up and running on a cutting edge GPU server.

AI, facial recognition, deep learning and other resource-intensive computing projects require the processing power of GPUs. Many startups relying on these high-power computing solutions have discovered that the costs of renting GPU instances in the cloud can be quite expensive and at times unpredictable.

However, when considering the upfront costs of buying GPU hardware, renting vs owning is a serious consideration that requires more in-depth analysis for a startup that may or may not be well-funded upfront.

Located in Central Illinois, we are close enough to Chicago's major national airports to be easily accessible within a couple hours drive. We are also far enough away from Chicago to provide a safe distance to protect your investment.

Why GPU?

GPU-accelerated computing is the use of a graphics processing unit (GPU) together with a CPU to accelerate a wide variety of applications, including those used for machine learning, data analytics, advanced modeling and much more. GPU accelerators are now being used in government labs, universities, enterprises, and small-and-medium businesses around the world. GPU based servers represent the next major revolution in enterprise-grade compute power and efficiency.

GPU accelerators have huge potential to bring new levels of performance to a wide array of organizations and their projects. Whether you are running dedicated machines, virtualizing or utilizing a hybrid configuration, a GPU server can drastically accelerate your performance.

Applications

There are currently over 400 applications that are compatible with GPU-accelerators and the list continues to grow daily. Just to name a few: Caffe, TensorFlow, Torche, and Matlab are all currently being used by organizations on GPU accelerated machines. Regardless of what you are doing there is a good chance that it can enhanced via the use of a GPU.

Performance

GPU’s use their massive parallel processing power to run a huge number of smaller tasks concurrently. Workloads that would normally be limited by the architecture of a CPU can be massively accelerated by a GPU based server. Parallel GPU dedicated server architecture help optimize workloads and drive down costs. Run your high intensity applications with a GPU enabled instance and experience unparalleled compute performance.