AI in Greece
AI in Greece: Server Configuration & Deployment
This article details the server configuration required for deploying Artificial Intelligence (AI) applications within a Greek infrastructure, focusing on optimal performance and scalability. It is intended as a guide for newcomers to our MediaWiki site and assumes a basic understanding of server administration and AI concepts.
Overview
The deployment of AI solutions in Greece presents unique challenges and opportunities. Considerations include bandwidth availability, data sovereignty regulations (GDPR compliance is crucial), and the need for cost-effective solutions. This document outlines a recommended server configuration addressing these concerns. We will cover hardware, software, networking, and security aspects. This setup is designed to support a range of AI workloads, including Machine Learning, Deep Learning, and Natural Language Processing.
Hardware Configuration
Selecting the appropriate hardware is paramount. The following table details a recommended baseline configuration for a single AI server node. This can be scaled horizontally by adding more nodes as needed. Remember to consult Server Sizing guidelines for specific workload requirements.
| Component | Specification | Notes |
|---|---|---|
| CPU | Dual Intel Xeon Gold 6338 (32 Cores/64 Threads) | High core count essential for parallel processing. Consider AMD EPYC alternatives. |
| RAM | 256GB DDR4 ECC Registered 3200MHz | Sufficient RAM for large datasets and model training. |
| Storage | 2 x 4TB NVMe PCIe Gen4 SSD (RAID 1) + 16TB HDD (Data Archive) | NVMe for fast data access. HDD for cost-effective long-term storage. |
| GPU | 2 x NVIDIA A100 80GB | Crucial for accelerated AI workloads. Alternatives include NVIDIA RTX A6000 or AMD Instinct MI250X. See GPU Selection. |
| Network Interface | Dual 100GbE Network Cards | High bandwidth for data transfer and distributed training. |
| Power Supply | 2000W Redundant Power Supplies | Ensures uptime and reliability. |
Software Stack
The software stack is equally important. We recommend a Linux-based operating system for its flexibility and open-source nature. Detailed instructions on Linux Server Setup are available elsewhere on this wiki.
| Software | Version | Purpose |
|---|---|---|
| Operating System | Ubuntu Server 22.04 LTS | Stable and widely supported Linux distribution. |
| CUDA Toolkit | 12.2 | NVIDIA's parallel computing platform and API. Required for GPU acceleration. |
| cuDNN | 8.9.2 | NVIDIA's Deep Neural Network library. Optimizes deep learning performance. See CUDA Installation. |
| Python | 3.10 | Primary programming language for AI development. |
| TensorFlow / PyTorch | 2.12 / 2.0 | Popular deep learning frameworks. Choose based on project requirements. Refer to Framework Comparison. |
| Docker | 24.0.5 | Containerization platform for consistent deployment. |
| Kubernetes | 1.27 | Container orchestration platform for scalability and management. See Kubernetes Deployment. |
Networking & Security
A robust network and stringent security measures are vital. Bandwidth limitations in certain areas of Greece must be considered.
| Area | Configuration | Details |
|---|---|---|
| Network Topology | Virtual Private Cloud (VPC) within a Greek data center. | Provides isolation and security. |
| Firewall | iptables/nftables with strict rules. | Controls network access and prevents unauthorized connections. Refer to Firewall Configuration. |
| Intrusion Detection System (IDS) / Intrusion Prevention System (IPS) | Snort/Suricata | Monitors network traffic for malicious activity. |
| Data Encryption | AES-256 encryption for data at rest and in transit. | Protects sensitive data from unauthorized access. |
| Access Control | Role-Based Access Control (RBAC) with multi-factor authentication. | Limits access to resources based on user roles. |
| Backup & Disaster Recovery | Regular backups to a geographically separate location. | Ensures data availability in case of a disaster. See Backup Strategies. |
Scalability & Future Considerations
The initial configuration can be scaled horizontally by adding more server nodes. Consider using a distributed training framework like Horovod or Ray to leverage the combined processing power of multiple GPUs. Future upgrades should focus on newer GPU generations (e.g., NVIDIA H100) and faster networking technologies (e.g., 400GbE). Monitoring tools like Prometheus and Grafana are essential for tracking performance and identifying bottlenecks. Explore cloud-based AI services offered by providers with data centers in Greece to potentially reduce infrastructure management overhead.
Server Management AI Deployment Data Storage Network Security GPU Computing Cloud Computing Database Administration System Monitoring Performance Tuning Virtualization Containerization Disaster Recovery GDPR Compliance Server Hardware System Administration
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.* ⚠️