The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning into the hands of engineers and data scientists. DIGITS can be used to rapidly train the highly accurate deep neural network (DNNs) for image classification, segmentation and object detection tasks.
This application relies heavily on the GPU to perform calculations, therefore a processor with a low core count and low clockspeed is acceptable.
The RTX 2080Ti become the defacto graphics card for deep learning and DIGITS offsets all the computing of data to the GPU. For maximum performance, recommend two NVIDIA GeForce RTX 2080Ti graphics cards.
This application relies more on reading data than writing data as it analyzes and processes training datasets. Extreme read rates are not required however, therefore we recommend a 512GB SSD for the operating system and program files. Furthermore, because deep learning requires large datasets to be processed, storing this data locally is important. Therefore a 4TB, 6TB or 8TB hard drive (or multiple hard drives) is recommended depending on your storage needs.
Benchmarks indicate that DIGITS performs best when the amount of system memory is double (or more) the graphics card memory. So if you have one Titan Xp card (which is 12GB), then we recommended 32GB RAM. If you have two Titan Xp cards (24GB), then we recommended 64GB RAM.
Recommended Hardware References
Running additional applications on this system?
The recommended components and configurations provided on this page are specific to this software. If you plan on running other applications, please view our recommendations for them as well and choose a configuration that best suits the needs of the application requirements collectively. Feel free to contact us for further assistance.