Today, containers are an easy way to deploy GPU accelerated libraries on development environment. RAPIDS is a set of DataScience libraries accelerated on GPU available today to a data scientist within an organization. Deploying RAPIDS on cloud in containers hepls democratizing access to accelerated computing. Deploying these containers in data centers on vGPUs help maximize hardware utilization and optimize budget-driven capital expenditures by sharing hardware resources among a team of users. With GPU-accelerated CUDA-X AI, data scientists can realize value from insights faster than with CPUs systems.
Data is changing the way companies do business, driving demand for data scientists and increasing complexity in their workflows. NVIDIA virtual GPU solutions in the data center and the cloud maximizes productivity and performance for data processing, machine learning, and a variety of other data science workloads. NVIDIA RTX capable GPUs and NVIDIA virtualization software along with VMware vSphere provide data scientists the performance they need to transform massive amounts of data into insights and create amazing user experiences in a virtual environment. Learn how you can use NVIDIA RAPIDS for executing end-to-end data science training pipelines using VMware ESXi hypervisor powered by NVIDIA virtual GPU solutions. Bring the power of power of GPU acceleration and maximize data science productivity of your data centers today.