With high memory bandwidth and efficient data transfer capabilities, GPUs significantly improve the processing and manipulation of large data sets, leading to faster and more efficient data analytics.
The superior performance of GPUs is perfectly suited for compute-intensive workloads, such as dynamic programming algorithms, video rendering, and scientific simulations.
GPUs are ideal for handling the high computational demands of deep neural networks and recurrent neural networks, which are essential for developing sophisticated deep learning models, including generative AI.
GPUs, with their thousands of processing cores, excel at performing multiple matrix operations and calculations simultaneously. This parallel processing capability allows GPUs to complete AI training tasks much faster than traditional CPUs.
This server oversees all the other servers in the cluster. You have full SSH access to this server, allowing you to manage the infrastructure and run your models directly.
Used for performing calculations during model training, this server is not directly accessible to you. It receives commands from the Poplar server. Availability of this server type may vary by location.
The virtual Intelligence Processing Unit (vIPU) service configures M2000/Bow-2000 servers to form a cluster. It plays a role during cluster creation and reconfiguration (e.g., resizing partitions). You can access the vIPU controller via API to manage and rebuild the cluster as needed.