AI in Liechtenstein
- AI in Liechtenstein: Server Configuration & Infrastructure
This article details the server configuration required to support Artificial Intelligence (AI) initiatives within Liechtenstein. It’s geared towards newcomers to our MediaWiki and provides a technical overview of the infrastructure needed. This document assumes a basic understanding of server administration and networking concepts.
Overview
Liechtenstein, while a small nation, is increasingly focused on leveraging AI for economic growth and innovation. Supporting this requires a robust and scalable server infrastructure. This document outlines the key components, configurations, and considerations for building such a system. We will cover hardware specifications, software stacks, networking requirements, and security protocols. This setup is designed to handle machine learning workloads, data processing, and the deployment of AI-powered applications. See also: Data Security Practices and Network Topology.
Hardware Specifications
The core of our AI infrastructure relies on high-performance servers capable of handling computationally intensive tasks. The following table details the specifications for our primary AI server cluster:
| Component | Specification | Quantity |
|---|---|---|
| CPU | Dual Intel Xeon Platinum 8380 (40 cores/80 threads per CPU) | 6 |
| RAM | 512 GB DDR4 ECC Registered 3200MHz | 6 |
| GPU | NVIDIA A100 80GB PCIe 4.0 | 4 per server |
| Storage (OS) | 1TB NVMe PCIe Gen4 SSD | 6 |
| Storage (Data) | 100TB NVMe PCIe Gen4 SSD RAID 10 | 1 |
| Network Interface | 2 x 100GbE Mellanox ConnectX-6 | 6 |
These servers are housed in a secure data center with redundant power and cooling. A separate cluster of servers (detailed below) is dedicated to data storage and preprocessing. Consider reviewing our Data Center Standards document for further details.
Data Storage & Preprocessing Servers
Efficient data storage and preprocessing are critical for successful AI projects. We utilize a separate cluster of servers dedicated to these tasks. This cluster focuses on high-capacity storage and fast data access.
| Component | Specification | Quantity |
|---|---|---|
| CPU | Intel Xeon Gold 6338 (32 cores/64 threads) | 4 |
| RAM | 256 GB DDR4 ECC Registered 3200MHz | 4 |
| Storage | 200TB SAS 12Gbps 7.2K RPM HDD RAID 6 | 1 |
| Network Interface | 2 x 40GbE Mellanox ConnectX-5 | 4 |
This storage cluster utilizes a distributed file system (see Distributed File Systems) to provide scalability and redundancy. Data preprocessing pipelines are run on these servers to prepare data for use in machine learning models. See also: Data Pipeline Architecture.
Software Stack
The software stack is crucial for managing the AI infrastructure and running AI applications. We utilize a combination of open-source and commercial software.
| Software | Version | Purpose |
|---|---|---|
| Operating System | Ubuntu Server 22.04 LTS | Base operating system for all servers |
| Containerization | Docker 20.10 | Containerizing AI applications |
| Orchestration | Kubernetes 1.25 | Managing and scaling containerized applications |
| Machine Learning Frameworks | TensorFlow 2.12, PyTorch 2.0 | Developing and training AI models |
| Data Science Libraries | Pandas, NumPy, Scikit-learn | Data manipulation and analysis |
| Monitoring | Prometheus, Grafana | Monitoring server performance and application health |
All servers are managed using configuration management tools like Ansible to ensure consistency and automation. We also utilize a centralized logging system (see Centralized Logging ) for troubleshooting and auditing.
Networking Configuration
The network infrastructure must support the high bandwidth requirements of AI workloads. We employ a dedicated, high-speed network for the AI cluster. This network is isolated from the general corporate network for security reasons.
- **Network Topology:** Spine-leaf architecture for low latency and high throughput.
- **Interconnect:** 100GbE connections between servers within the AI cluster.
- **Firewall:** A dedicated firewall (see Firewall Configuration) protects the AI cluster from external threats.
- **Load Balancing:** Load Balancing Techniques are used to distribute traffic across multiple servers.
- **DNS:** Internal DNS servers resolve hostnames within the AI cluster.
Security Considerations
Security is paramount when dealing with sensitive data used in AI applications. We implement multiple layers of security:
- **Access Control:** Role-Based Access Control (RBAC) restricts access to resources based on user roles. See RBAC Implementation.
- **Data Encryption:** Data is encrypted both in transit and at rest.
- **Intrusion Detection:** An intrusion detection system (IDS) monitors the network for malicious activity.
- **Regular Security Audits:** Regular security audits are conducted to identify and address vulnerabilities.
- **Vulnerability Scanning:** Automated vulnerability scanning is employed to identify and mitigate potential security risks.
Future Scalability
The infrastructure is designed to be scalable to accommodate future growth. We plan to add more servers to the AI cluster as needed. We are also exploring the use of cloud-based AI services (see Cloud Integration) to supplement our on-premise infrastructure.
Server Maintenance Schedule Troubleshooting Guide Contact Information
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.* ⚠️