Whitepaper:
Using NVIDIA Virtual GPUs to power mixed workloads
How to accelerate your organization’s innovations with faster performance and smoother workflows.
The high demand for professional applications means there are more use cases for GPUs across the enterprise than ever before.
Designers and engineers rely on graphics-intensive applications featuring 3D visualization, many of which include AI enhancements. Data scientists run compute-intensive applications powered by AI, deep learning, and inference. Knowledge workers are using increasingly graphics-intensive office productivity applications —resulting in a 20% increase in GPU consumption alone.
Processing data with GPUs exponentially speeds up these applications, improving performance and helping companies innovate faster. However, professionals using highly specialized applications still experience productivity setbacks. Many workflows are frequently slowed by inefficiencies in the data center and the limitations of physical workstations.
The innovative enterprise is now looking for IT solutions that can significantly speed up professional workflows so that decisions can be made faster and better. What it needs is a flexible IT infrastructure that seamlessly delivers better GPUs utilization to satisfy more business needs with less resources and investment.
