AI in Cyprus
```wiki ⧼server-article-title⧽
AI in Cyprus: Server Configuration and Infrastructure
This article details the server configuration supporting Artificial Intelligence (AI) initiatives within Cyprus. It’s aimed at newcomers to our server infrastructure and provides a technical overview of the hardware and software employed. Understanding this setup is crucial for developers, system administrators, and anyone contributing to AI projects hosted here. We will cover hardware specifications, software stacks, network topology, and security considerations. This document assumes a basic understanding of server administration and networking concepts.
Hardware Overview
The core of our AI infrastructure relies on a cluster of high-performance servers located in a secure data center near Limassol. These servers are specifically chosen for their processing power, memory capacity, and suitability for machine learning workloads. Redundancy is a key design principle, ensuring high availability and minimizing downtime.
| Server Role | Model | CPU | RAM | Storage | GPU |
|---|---|---|---|---|---|
| Master Node (Cluster Management) | Dell PowerEdge R750 | 2 x Intel Xeon Gold 6338 | 256 GB DDR4 ECC | 2 x 1 TB NVMe SSD (RAID 1) | NVIDIA Quadro RTX A4000 |
| Worker Node 1-4 (Training) | HP ProLiant DL380 Gen10 | 2 x AMD EPYC 7763 | 512 GB DDR4 ECC | 4 x 4 TB SAS HDD (RAID 5) | 4 x NVIDIA A100 (40GB) |
| Inference Node 1-3 (Deployment) | Supermicro SYS-2029U-TR4 | 2 x Intel Xeon Silver 4310 | 128 GB DDR4 ECC | 1 x 2 TB NVMe SSD | NVIDIA Tesla T4 |
This table provides a summary of the key hardware components. Detailed specifications for each model can be found on the respective vendor websites: Dell, HP, and Supermicro. The selection of GPUs is particularly important, as they accelerate the computationally intensive tasks associated with AI model training and inference. Regular hardware audits are conducted by the IT Department.
Software Stack
The software environment is built on a foundation of Linux, leveraging containerization technologies for efficient resource utilization and deployment. We primarily use Ubuntu Server 22.04 LTS as the operating system for all servers.
| Layer | Software | Version | Purpose | |||
|---|---|---|---|---|---|---|
| Operating System | Ubuntu Server | 22.04 LTS | Base OS for all servers | |||
| Containerization | Docker | 20.10 | Packaging and running applications in containers | |||
| Orchestration | Kubernetes | 1.26 | Managing and scaling containerized applications | |||
| Machine Learning Frameworks | TensorFlow | 2.12 | Deep learning framework | PyTorch | 2.0 | Deep learning framework |
| Programming Languages | Python | 3.10 | Primary language for AI development |
The choice of TensorFlow and PyTorch allows developers flexibility in selecting the best framework for their specific AI tasks. We also utilize JupyterHub for interactive data science and machine learning development. The entire software stack is managed using Ansible for automated configuration and deployment. Detailed documentation on our internal software repositories is available on the Internal Wiki.
Network Topology and Security
The servers are interconnected via a dedicated 10 Gigabit Ethernet network. This high-bandwidth connection ensures fast data transfer between nodes during training and inference. A firewall, managed by the Network Security Team, protects the cluster from unauthorized access.
| Component | Details |
|---|---|
| Network Type | Dedicated 10 Gigabit Ethernet |
| Firewall | FortiGate 60F |
| Intrusion Detection System (IDS) | Snort |
| VPN Access | OpenVPN |
| Internal DNS | Bind9 |
Access to the servers is strictly controlled through SSH keys and multi-factor authentication. Regular security audits and penetration testing are performed to identify and address vulnerabilities. All data is encrypted both in transit and at rest. We adhere to the Cyprus Data Protection Law regarding data privacy and security. The Disaster Recovery Plan outlines procedures for data backup and restoration in the event of a system failure. We also implement robust Logging and Monitoring using tools like Prometheus and Grafana. The Security Incident Response Team is responsible for handling any security breaches.
Future Expansion
We are planning to expand the AI infrastructure with the addition of more GPU servers and increased storage capacity. We are also exploring the use of specialized AI accelerators, such as TPUs, to further improve performance. The Roadmap for AI Infrastructure details these planned enhancements. The current project, Project Phoenix, aims to incorporate edge computing capabilities for real-time AI processing.
Limassol
Dell
HP
Supermicro
Ubuntu Server
Docker
Kubernetes
TensorFlow
PyTorch
JupyterHub
Ansible
Internal Wiki
IT Department
Cyprus Data Protection Law
Disaster Recovery Plan
Logging and Monitoring
Security Incident Response Team
Network Security Team
Roadmap for AI Infrastructure
Project Phoenix
```
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 |
Order Your Dedicated Server
Configure and order your ideal server configuration
Need Assistance?
- Telegram: @powervps Servers at a discounted price
⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️