Teaching Equipment Hardware and software specifications related to deploying JupyterHub for instructional purposes are provided as follows: 1. Login/Storage Server: CPU 1xAMD EPYC 7413. Memory 128 GB. OS Drive 2T NVMe SSD. Data Drive 8x16T SATA HDD. GPU. Network Card 10 Gb Ethernet Card Dual Port. OS Ubuntu 22.04. Software o JupyterHub Tech Stack: K8’cluster, Proxy server (NGINX), Docker spawner, Python3.11. o Containerization and Virtualization: Support for Docker and Kubernetes for containerized workflows o Security: Hardware-based encryption (TPM 2.0), secure boot. PSU (power supply) 1+1 1000w PSU with redundancy. Chassis 1U Or 2U rackmount server with rack rails. Quantity of Server 1; 2. RTX 6000 Ada GPU Server: CPU 2xAMD EPYC 9354. Memory 576 GB DDR5 ECC. OS Drive 4T NVMe SSD. Data Drive 8T NVMe SSD. GPU 8xRTX 6000 Ada 48GB. Cooling Air cooling with optional liquid-cooling retrofits for data center deployment. Network Card 10 Gb Ethernet Card Dual Port. OS Ubuntu 22.04. Software o JupyterHub Tech Stack: K8’cluster, Proxy server (NGINX), Docker spawner, Python3.11. o ML/AI Libraries: Pre-installed with TensorFlow, PyTorch, Keras o Containerization and Virtualization: Support for Docker and Kubernetes for containerized workflows o NVIDIA AI Enterprise: Optimized driver and CUDA support o Security: Hardware-based encryption (TPM 2.0), secure boot...
