Enormous computing power for the most demanding High Performance Computing systems.
Configure GPU servers with NVIDIA latest GPU products, like Nvidia Tesla V100 or Nvidia A100 with GPU-Direct options.
Generating massively parallel processing power and unrivaled networking flexibility, these systems deliver the highest quality with extreme optimization for the most computationally-intensive applications like Artificial Intelligence & Machine Learning, Visual/Media Editing, Financial Simulations, Astrophysics, etc.
2 items available
GPU SuperServer SYS-1029GQ-TNRT
Big Data Analytics
Research Lab, Astrophysics4 487.25 €
GPU SuperServer SYS-1029GQ-TRT
GPU Server, Mission-critical app.
enterprise server, HPC
oil & gas, financial, 3D rendering
chemistry4 378.65 €
2 items available
Manufacturers design GPUs for fast 3-D processing, accurate floating-point arithmetic, and error-free number crunching. Although they typically operate at slower clock speeds, they have thousands of cores that enable them to execute thousands of individual threads simultaneously. GPU servers, as the name suggests, are servers packed with graphics cards, designed to harness this raw processing power. Using an offloading process, the CPU can hand specific tasks to the GPUs, increasing performance. Running computationally intensive tasks on a CPU can tie up the whole system. Offloading some of this work to a GPU is a great way to free up resources and maintain consistent performance. Interestingly, you can just send the toughest workloads to your GPU while the CPU handles the main sequential processes. Such GPU strategies are critical to delivering better services that cater to end-users, who experience accelerated performance. Many of the Big Data tasks that create business value involve performing the same operations repetitively. The wealth of cores available in GPU server hosting lets you conduct this kind of work by splitting it up between processors to crunch through voluminous data sets at a quicker rate. Also, these GPU-equipped systems use less energy to accomplish the same tasks and place lower demands on the supplies that power them. In specific use cases, a GPU can provide the same data processing ability of 400 servers with CPU only.