AI in Godalming

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  1. AI in Godalming: Server Configuration Documentation

This document details the server configuration for the "AI in Godalming" project, a localized artificial intelligence initiative focused on data analysis for local council services. This guide is intended for new system administrators and developers contributing to the project. Please read this document thoroughly before making any changes to the server environment. Familiarity with Linux server administration and MediaWiki administration is highly recommended.

Overview

The "AI in Godalming" project utilizes a cluster of servers hosted in a dedicated data center in Guildford. The primary goal is to process and analyze publicly available data, combined with anonymized council data, to improve resource allocation and service delivery. The system leverages machine learning algorithms, requiring considerable processing power and storage capacity. This document will cover the hardware, software, and network configuration of these servers. We utilize Debian Linux as our base operating system for stability and security.

Hardware Specifications

The server cluster consists of three main types of servers: Database Servers, Application Servers, and Processing Nodes. The following tables detail the specifications of each type.

Server Type CPU RAM Storage Network Interface
Database Servers (2x) Intel Xeon Gold 6248R (24 cores) 256 GB DDR4 ECC 4 x 4TB NVMe SSD (RAID 10) 10 Gbps Ethernet
Application Servers (3x) AMD EPYC 7543P (32 cores) 128 GB DDR4 ECC 2 x 2TB NVMe SSD (RAID 1) + 8TB HDD 1 Gbps Ethernet
Processing Nodes (5x) NVIDIA A100 GPU + Intel Xeon Silver 4210 (10 cores) 64 GB DDR4 ECC 1 x 1TB NVMe SSD 10 Gbps Ethernet + 10 Gbps InfiniBand

Regular hardware monitoring is performed using Nagios to ensure optimal performance and identify potential failures. Access to the hardware is restricted to authorized personnel only; see the Security Policy for details.

Software Configuration

All servers are running Debian 11 (Bullseye) with a customized kernel optimized for machine learning workloads. The following software components are crucial to the system's operation.

Software Component Version Server Type Purpose
PostgreSQL 14.5 Database Servers Data storage and retrieval.
Python 3 3.9.7 All Servers Primary scripting language for AI models.
TensorFlow 2.8.0 Processing Nodes Machine learning framework.
PyTorch 1.12.1 Processing Nodes Alternative machine learning framework.
Nginx 1.21.3 Application Servers Web server and reverse proxy.
Gunicorn 20.1.0 Application Servers Python WSGI HTTP server.

Software updates are managed using APT package management. A robust backup strategy is in place, utilizing daily full backups and hourly incremental backups to a remote storage location. Configuration management is handled with Ansible to ensure consistency across all servers.

Network Configuration

The server cluster is connected to the internal network via a dedicated VLAN. A firewall, configured using iptables, protects the servers from unauthorized access.

Network Component IP Address Range Purpose
VLAN 100 (AI Cluster) 192.168.100.0/24 Internal network for AI servers.
Database Servers 192.168.100.10-11 Host PostgreSQL databases.
Application Servers 192.168.100.20-22 Serve web applications and APIs.
Processing Nodes 192.168.100.30-34 Perform machine learning computations.
Load Balancer 192.168.100.1 Distributes traffic to application servers.

Access to the servers from the external network is restricted to specific ports and IP addresses, as defined in the Firewall Rules. The load balancer distributes traffic across the application servers to ensure high availability and scalability. We use DNS records to map domain names to the load balancer's IP address. The network is monitored using Zabbix for performance and security.


Security Considerations

Security is paramount. All servers are hardened according to the CIS Benchmarks. Regular security audits are conducted to identify and address vulnerabilities. User access is controlled via SSH keys and multi-factor authentication. All data is encrypted both in transit and at rest. The Incident Response Plan outlines procedures for handling security breaches.


Main Page Server Administration Database Administration Network Security Machine Learning Data Analysis System Monitoring Backup and Recovery Configuration Management Firewall Configuration Security Policy Incident Response Plan APT package management Nagios Zabbix DNS records IPTables


Intel-Based Server Configurations

Configuration Specifications Benchmark
Core i7-6700K/7700 Server 64 GB DDR4, NVMe SSD 2 x 512 GB CPU Benchmark: 8046
Core i7-8700 Server 64 GB DDR4, NVMe SSD 2x1 TB CPU Benchmark: 13124
Core i9-9900K Server 128 GB DDR4, NVMe SSD 2 x 1 TB CPU Benchmark: 49969
Core i9-13900 Server (64GB) 64 GB RAM, 2x2 TB NVMe SSD
Core i9-13900 Server (128GB) 128 GB RAM, 2x2 TB NVMe SSD
Core i5-13500 Server (64GB) 64 GB RAM, 2x500 GB NVMe SSD
Core i5-13500 Server (128GB) 128 GB RAM, 2x500 GB NVMe SSD
Core i5-13500 Workstation 64 GB DDR5 RAM, 2 NVMe SSD, NVIDIA RTX 4000

AMD-Based Server Configurations

Configuration Specifications Benchmark
Ryzen 5 3600 Server 64 GB RAM, 2x480 GB NVMe CPU Benchmark: 17849
Ryzen 7 7700 Server 64 GB DDR5 RAM, 2x1 TB NVMe CPU Benchmark: 35224
Ryzen 9 5950X Server 128 GB RAM, 2x4 TB NVMe CPU Benchmark: 46045
Ryzen 9 7950X Server 128 GB DDR5 ECC, 2x2 TB NVMe CPU Benchmark: 63561
EPYC 7502P Server (128GB/1TB) 128 GB RAM, 1 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (128GB/2TB) 128 GB RAM, 2 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (128GB/4TB) 128 GB RAM, 2x2 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (256GB/1TB) 256 GB RAM, 1 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (256GB/4TB) 256 GB RAM, 2x2 TB NVMe CPU Benchmark: 48021
EPYC 9454P Server 256 GB RAM, 2x2 TB NVMe

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