AI in West Midlands

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AI in West Midlands: Server Configuration Guide

This article details the server configuration supporting the "AI in West Midlands" project. It's aimed at newcomers to the wiki and provides a technical overview of the hardware and software used. Understanding this setup is crucial for contributing to the project's development and maintenance. Please refer to our Deployment Guidelines for general contribution information.

Overview

The "AI in West Midlands" project utilizes a distributed server infrastructure to handle the computational demands of machine learning model training, inference, and data processing. This infrastructure is primarily hosted within a secure data centre in Birmingham, with some edge deployments for real-time applications. The system architecture is based on a microservices approach, detailed in our Microservices Architecture Document. We leverage a combination of bare-metal servers and virtual machines (VMs) for flexibility and scalability. This design allows for efficient resource allocation and caters to the varying needs of different AI tasks. See also Scalability Considerations.

Hardware Configuration

The core of the AI infrastructure consists of several server nodes, categorized by their primary function. Below are detailed specifications for each type.

Primary Training Servers

These servers are dedicated to training large AI models. They require significant computational power and memory.

Specification Value
CPU 2 x AMD EPYC 7763 (64-core)
RAM 512 GB DDR4 ECC Registered
GPU 8 x NVIDIA A100 80GB PCIe
Storage 4 x 8TB NVMe SSD (RAID 0)
Network 2 x 100GbE
Operating System Ubuntu 22.04 LTS

These servers utilize GPU virtualization to maximise resource usage and are monitored through our Monitoring Dashboard.

Inference Servers

These servers are optimized for low-latency inference, serving predictions from trained models.

Specification Value
CPU 2 x Intel Xeon Gold 6338 (32-core)
RAM 256 GB DDR4 ECC Registered
GPU 4 x NVIDIA T4 16GB PCIe
Storage 2 x 4TB NVMe SSD (RAID 1)
Network 2 x 25GbE
Operating System CentOS Stream 9

The inference servers are deployed using Kubernetes for orchestration and autoscaling. See the Inference Pipeline Documentation for details on model deployment.

Data Storage Servers

These servers provide centralized storage for datasets and model artifacts.

Specification Value
CPU 2 x Intel Xeon Silver 4310 (12-core)
RAM 128 GB DDR4 ECC Registered
Storage 32 x 16TB SAS HDD (RAID 6)
Network 2 x 40GbE
Operating System Red Hat Enterprise Linux 8

Data is accessed via a Network File System (NFS) and secured with strict access controls described in the Security Policy.

Software Stack

The software stack is built around open-source technologies, ensuring flexibility and cost-effectiveness.


Network Topology

The server infrastructure is connected via a high-speed, low-latency network. A dedicated VLAN is used for inter-server communication. Firewall rules are configured to restrict access to only necessary ports and services. Please consult the Network Diagram for a visual representation. The network is also segmented using Virtual LANs for improved security.

Security Considerations

Security is paramount. All servers are protected by firewalls, intrusion detection systems, and regular security audits. Access to servers is restricted to authorized personnel only, governed by the Access Control List. Data is encrypted both in transit and at rest. See the Security Best Practices document for detailed security guidelines.


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.* ⚠️