Technology advances, more teams, and organizations are implementing machine learning/ deep learning operations. So these days, people are looking for ways to speed up processes. Graphics processing units (GPUs) and other hardware accelerators can dramatically reduce the time taken to train complex machine learning models. Training models for tasks like image classification, ticket classification, video analysis, and natural language processing involve compute-intensive matrix multiplication and other operations that can take advantage of a GPU’s massively parallel architecture. This process can take days or even months to run on a single processor. However, if the power of multiple GPUs can be utilized to offload these tasks, training time will be reduced to hours instead of days or months.

GPU Cloud for AI at iRender provides you with state-of-the-art GPUs to speed up your compute tasks like machine learning, deep learning. A wide selection of GPUs is available to match your needs. To optimize your workload, every server image is preinstalled with major AI frameworks such as TensorFlow, Jupyter Notebook, and CUDA drivers. Now, enjoy your training tasks at iRender.