By Department of Nanoscale Science & Engineering, University at Albany
For final machine learning operations (training on bulk images) the xCITE Lab has a fourth, much more powerful “big iron” system in the ultra-high-end AI Deep Learning server (DGX-1). The server is housed in the University at Albany’s Tier-3 Data Center, and managed/maintained by the xCITE laboratory. - Deep learning frameworks with pre-installed libraries 100s of pre-configured models available instantly - Containerization tools to provide fully built and pre-configured environments for instant use Industry leading deep learning and accelerated analytics applications - Resources to implement deep learning algorithms, using weather data on some of the fastest machines currently available - Access to massive parallel graphics processors providing higher throughput for compute intensive workloads at a fraction of the cost - No hidden fees for data transfers and storage - Docker swarm with resource management - Docker image customization Isolation of individual containers and GPUs The DGX-1 V100 system contains 8 Tesla V100 GPUs with a combined total of 40,960 CUDA (graphics) cores, 5120 Tensor cores, 256GB of GPU memory, and 1TB of RAM/system memory all linked by NVIDIAs 300GB/s NVLINK interconnect. The system employs dual 20-core Intel Xeon E5-2698 v4 CPUs running at 2.2GHz, and has 68TB of SSD storage configured in RAID 6 for redundancy and speed.
