AI in Newcastle upon Tyne
AI in Newcastle upon Tyne: Server Configuration Overview
This article details the server configuration supporting Artificial Intelligence (AI) initiatives within Newcastle upon Tyne. It is designed for newcomers to our MediaWiki environment and provides a technical overview of the hardware and software utilized. This infrastructure supports a variety of AI research and development projects, including Natural Language Processing, Computer Vision, and Machine Learning. Understanding this setup is crucial for anyone contributing to or utilizing these resources.
Introduction
Newcastle upon Tyne is rapidly becoming a hub for AI innovation. This requires robust and scalable server infrastructure. The following sections outline the key components of this infrastructure, focusing on hardware specifications, software stacks, and networking considerations. This setup is designed for both research and potential future production deployment of AI-driven services. We prioritize scalability, redundancy, and high performance. Understanding the Data Storage solutions is also vital.
Hardware Specifications
The core of our AI infrastructure comprises a cluster of high-performance servers. These servers are distributed across two geographically separate data centers within Newcastle upon Tyne for redundancy and disaster recovery. Each data center houses an identical configuration of servers. The specifications are detailed below.
| Component | Specification (Per Server) | Quantity (Total) |
|---|---|---|
| CPU | 2 x Intel Xeon Gold 6338 (32 cores/64 threads) | 24 |
| RAM | 256GB DDR4 ECC Registered 3200MHz | 24 |
| GPU | 4 x NVIDIA A100 80GB | 96 |
| Storage (OS) | 1TB NVMe SSD | 24 |
| Storage (Data) | 8 x 16TB SAS HDD (RAID 6) | 192 |
| Network Interface | 2 x 100Gbps Ethernet | 24 |
This configuration allows for parallel processing of large datasets and complex AI models. The high-bandwidth network connectivity is essential for inter-server communication and data transfer. We also utilize Network Load Balancing to distribute workloads efficiently.
Software Stack
The software stack is built around a Linux operating system and a suite of AI frameworks and tools. We prioritize open-source software to maximize flexibility and minimize licensing costs.
| Layer | Software | Version |
|---|---|---|
| Operating System | Ubuntu Server 22.04 LTS | 22.04 |
| Containerization | Docker | 24.0.7 |
| Orchestration | Kubernetes | 1.28 |
| AI Frameworks | TensorFlow, PyTorch, Scikit-learn | 2.15.0, 2.1.0, 1.3.0 |
| Programming Languages | Python, R | 3.10, 4.3.1 |
| Data Science Tools | Jupyter Notebook, RStudio | Latest |
Kubernetes is used to manage and scale the deployment of AI applications. Docker containers provide a consistent and reproducible environment for development and deployment. Version Control is handled using Git. We also employ a robust Monitoring System to track server health and performance.
Networking and Security
The server infrastructure is connected via a dedicated 100Gbps fiber optic network. Security is a paramount concern, and we employ a multi-layered security approach.
| Area | Security Measure | Description |
|---|---|---|
| Network Security | Firewall | Configured to allow only necessary traffic. |
| Access Control | SSH Key Authentication | Password-based authentication is disabled. |
| Data Encryption | TLS/SSL | Used for all communication. |
| Intrusion Detection | Suricata | Monitors network traffic for malicious activity. |
| Vulnerability Scanning | Nessus | Regularly scans servers for vulnerabilities. |
All data is encrypted both in transit and at rest. Regular security audits are conducted to identify and address potential vulnerabilities. We also utilize Virtual Private Networks (VPNs) for secure remote access. Detailed Security Policies are available to all personnel. Proper Backup and Recovery procedures are also in place.
Future Expansion
We are continuously evaluating and upgrading our infrastructure to meet the growing demands of AI research and development. Future plans include:
- Increasing GPU capacity with the latest generation NVIDIA GPUs.
- Implementing a distributed file system for improved data access.
- Integrating with cloud-based AI services for enhanced scalability.
- Exploring the use of specialized hardware accelerators, such as TPUs.
- Improving our Disaster Recovery Plan.
Related Pages
- Server Room Access
- Data Backup Procedures
- Software Installation Guide
- Troubleshooting Common Issues
- Contact Support
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.* ⚠️