AI in Winchester

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  1. AI in Winchester

This article details the server configuration powering the "AI in Winchester" project, a local initiative utilizing machine learning to analyze historical records within the City of Winchester. This document is intended for other system administrators and developers contributing to the project, as well as newcomers seeking to understand the underlying infrastructure. This system leverages a hybrid approach, combining on-premise hardware with cloud-based services.

Overview

The "AI in Winchester" project requires significant computational resources for data processing, model training, and real-time inference. We've adopted a layered architecture: data ingestion and pre-processing occur locally, model training is primarily handled in the cloud to leverage scalable GPU resources, and inference is distributed between on-premise servers and cloud endpoints depending on latency requirements. The core on-premise infrastructure is housed within the Winchester City Hall data center. See Data Center Security Protocols for details on physical access and security.

Hardware Configuration

The core of the on-premise infrastructure consists of three primary servers – 'Athena', 'Hephaestus', and 'Demeter'. Each server has a specific role in the system.

Server Name Role CPU RAM Storage
Athena Data Ingestion & Pre-processing Intel Xeon Gold 6248R (24 cores) 128GB DDR4 ECC 2 x 4TB NVMe SSD (RAID 1)
Hephaestus Real-time Inference Engine AMD EPYC 7763 (64 cores) 256GB DDR4 ECC 4 x 2TB NVMe SSD (RAID 10)
Demeter Metadata Database & API Server Intel Xeon Silver 4210 (10 cores) 64GB DDR4 ECC 8 x 1TB SATA SSD (RAID 6)

These servers run Ubuntu Server 22.04 LTS, chosen for its stability, security updates, and widespread community support. Network connectivity is provided by a dedicated 10Gbps fiber link to the internet and a separate gigabit network for internal communication. Refer to the Network Diagram for a visual representation. Power redundancy is provided by a dual UPS system, detailed in Power Backup Systems.

Software Stack

The software stack is critical for the project’s success. We utilize a combination of open-source tools and custom-developed applications.

Component Version Description
Operating System Ubuntu Server 22.04 LTS The base operating system for all servers.
Python 3.10.6 Primary programming language for data science and machine learning.
TensorFlow 2.12.0 Machine learning framework used for model training and inference.
PostgreSQL 14.7 Relational database for storing metadata and historical records. See Database Schema.
Flask 2.2.2 Web framework for building the API server.
Nginx 1.23.3 Web server and reverse proxy.

Athena utilizes Apache Kafka for streaming data ingestion from various sources, including digitized historical documents and local sensor data. Hephaestus employs TensorFlow Serving to deploy and manage machine learning models for real-time inference. Demeter hosts the API built using Flask, which provides access to the metadata database and inference results. Monitoring is handled by Prometheus and Grafana, detailed in System Monitoring.

Cloud Integration

While much of the inference is handled locally, model training relies heavily on cloud resources. We utilize Amazon SageMaker for training large language models (LLMs) and other complex machine learning models. Data is securely transferred to and from the cloud using AWS S3 and encrypted using AES-256 encryption. Access control is managed through IAM roles and policies. Cost optimization strategies are outlined in Cloud Cost Management. The selection of AWS was documented in Cloud Provider Selection.

Security Considerations

Security is paramount. All servers are hardened according to Server Hardening Standards. Firewalls are configured using iptables to restrict access to essential ports. Regular security audits are conducted, as documented in Security Audit Reports. Data is encrypted at rest and in transit. User authentication is handled through LDAP integration with the City of Winchester’s directory services. We adhere to all relevant data privacy regulations, including GDPR Compliance.

Future Expansion

Planned future expansions include adding a dedicated GPU server to the on-premise infrastructure for faster model inference and increasing the storage capacity of Demeter to accommodate the growing historical record database. We are also exploring the use of Kubernetes for container orchestration to improve scalability and resilience.



Data Center Security Protocols Network Diagram Power Backup Systems Database Schema System Monitoring Server Hardening Standards Cloud Provider Selection Cloud Cost Management Security Audit Reports GDPR Compliance Ubuntu Server 22.04 LTS Apache Kafka TensorFlow Serving Flask Amazon SageMaker AWS S3 IAM roles iptables LDAP integration Kubernetes


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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