# NVIDIA GPU Selection and Configuration

PC system configuration choices directly affect tool processing speed without affecting tool accuracy or behavior, and they are the most expensive and hardest to predict the effect of.

Configuration Option | Why it's faster | Best value option | Watch out for...
--- | --- | --- | ---
NVIDIA device type | The number of CUDA cores is directly related to high-precision processing speed and training. The number of standard Tensor cores is directly related to processing speed and training speed. The number of Turing Tensor cores is related to processing speed in low-precision mode only. These cores do not affect standard precision processing or training speed. |  |
NVIDIA driver mode | Consumer-grade gaming-oriented NVIDIA devices only support the WDDM device driver model. This driver is intended to support graphics display, not computation. Professional-grade NVIDIA cards support the TCC driver mode, which provides better performance and stability. | Select a NVIDIA RTX / Quadro® or Tesla (or selected Titan)-branded NVIDIA card. | If using a GeForce-branded card, be aware that NVIDIA drivers are updated frequently and may not be compatible with Deep Learning. Using TCC mode driver prevents the use of Video output on the GPU card; use onboard video instead.
Optimized memory | Deep Learning optimized memory, which is enabled by default, improves performance by overriding the standard NVIDA GPU memory management system. | Make sure your card has at least 4GB of GPU memory. Performance improvement is not as significant for cards using the TCC driver. |