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AI in Andorra

# AI in Andorra: Server Configuration

This article details the server configuration used to support Artificial Intelligence (AI) workloads within the Andorran data center. It's aimed at newcomers to the server administration team and provides a technical overview of the hardware and software components. Understanding this configuration is crucial for maintenance, troubleshooting, and future scaling. This configuration is optimized for both training and inference tasks related to several ongoing AI projects, including Project Nightingale and Operation Pyrenees.

Overview

The AI infrastructure in Andorra is designed for high throughput, low latency, and scalability. It leverages a combination of powerful GPU servers, high-speed networking, and a distributed file system. The core principle behind the design is to provide a flexible platform capable of adapting to the rapidly evolving demands of AI research and deployment. We utilize a hybrid cloud approach, with some services running on-premise and others leveraging external providers like Andorra Cloud Services.

Hardware Specifications

The primary compute nodes are based on the following specifications:

Component Specification
CPU Dual Intel Xeon Platinum 8380 (40 cores/80 threads per CPU)
RAM 512GB DDR4 ECC Registered 3200MHz
GPU 8 x NVIDIA A100 80GB PCIe 4.0
Storage (OS) 1TB NVMe PCIe 4.0 SSD
Storage (Data) 16TB NVMe PCIe 4.0 SSD (RAID 0)
Networking 200Gbps InfiniBand

These servers are housed in dedicated racks with advanced cooling systems to maintain optimal operating temperatures. Power redundancy is provided by dual power supplies and an Uninterruptible Power Supply (UPS) system. See Power Management Procedures for details on UPS maintenance.

Networking Infrastructure

The network is a critical component of the AI infrastructure. It's designed to minimize latency and maximize bandwidth between compute nodes and the storage system.

Component Specification
Interconnect 200Gbps InfiniBand HDR
Switches Mellanox Spectrum-2
Router Cisco ASR 9000 Series
Firewall Palo Alto Networks PA-820
External Connectivity 100Gbps Dedicated Internet Connection

Network segmentation is implemented to isolate the AI infrastructure from other network segments, enhancing security. Refer to the Network Security Policy for detailed information on network security measures. We also utilize Virtual LANs (VLANs) for further segmentation.

Software Stack

The software stack is built around a Linux distribution optimized for AI workloads.

Component Specification
Operating System Ubuntu Server 22.04 LTS
Containerization Docker and Kubernetes
Machine Learning Frameworks TensorFlow, PyTorch, scikit-learn
Distributed File System Lustre
Job Scheduler Slurm
Monitoring Prometheus and Grafana

We employ a containerized environment using Docker and Kubernetes to facilitate deployment and scaling of AI applications. The Lustre distributed file system provides high-performance storage access for large datasets. See Lustre File System Management for more details. We also integrate with Version Control Systems (Git) for code management. The monitoring stack allows for real-time performance analysis and proactive identification of potential issues. Incident Response Protocol outlines procedures for addressing performance degradation.

Storage System

The storage system is designed to handle the massive datasets required for AI training.

⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️

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