AI in the Seychelles
- AI in the Seychelles: Server Configuration & Deployment
This article details the server configuration used to support Artificial Intelligence (AI) workloads within the Seychelles data center. It is aimed at newcomers to the MediaWiki site and provides a technical overview suitable for system administrators and developers. The infrastructure is designed for scalability, redundancy, and high performance, focusing on machine learning and data analysis tasks. This document covers hardware, software, networking, and security considerations.
Overview
The Seychelles facility serves as a strategic location for AI processing due to its stable power grid, robust network connectivity, and favorable climate for cooling. The current AI infrastructure comprises a cluster of high-performance servers dedicated to various AI applications, including image recognition, natural language processing, and predictive modeling. The entire system is monitored using Prometheus and visualized with Grafana. We utilize Kubernetes for orchestration. Data storage is handled by a dedicated team utilizing Ceph. Initial project specifications were based on the Seychelles AI Initiative.
Hardware Specifications
The core of our AI infrastructure consists of dedicated servers equipped with specialized hardware. The following table details the specifications for the primary compute nodes:
| Component | Specification |
|---|---|
| CPU | Dual Intel Xeon Gold 6338 (32 cores per CPU) |
| RAM | 512GB DDR4 ECC Registered @ 3200MHz |
| GPU | 4 x NVIDIA A100 (80GB HBM2e) |
| Storage (OS) | 1TB NVMe PCIe Gen4 SSD |
| Storage (Data) | 16TB NVMe PCIe Gen4 SSD (RAID 0) |
| Network Interface | Dual 100GbE Mellanox ConnectX-6 |
| Power Supply | Redundant 2000W 80+ Platinum |
These servers are housed in dedicated racks with advanced cooling systems to maintain optimal operating temperatures. We also have a smaller set of servers for development and testing. These servers utilize VirtualBox for virtualization.
Networking Infrastructure
The network infrastructure is crucial for ensuring high-bandwidth, low-latency communication between servers and external clients.
| Network Component | Specification |
|---|---|
| Core Switches | Arista 7050X Series (400GbE) |
| Top-of-Rack Switches | Cisco Nexus 9332C (100GbE) |
| Interconnect | Dark Fiber connection to major internet exchanges |
| Firewall | Palo Alto Networks PA-820 |
| Load Balancer | HAProxy |
The network is segmented using VLANs to isolate different AI workloads and enhance security. Network monitoring is performed using Nagios. Internal communication utilizes a dedicated private network. We adhere to RFC1918 for internal IP addresses.
Software Stack
The software stack is designed to provide a flexible and scalable platform for AI development and deployment.
| Software Component | Version |
|---|---|
| Operating System | Ubuntu 22.04 LTS |
| Containerization | Docker 23.0 |
| Orchestration | Kubernetes 1.27 |
| Machine Learning Frameworks | TensorFlow 2.12, PyTorch 2.0, scikit-learn 1.2 |
| Data Science Libraries | Pandas, NumPy, Matplotlib |
| Database | PostgreSQL 15 |
| Monitoring | Prometheus, Grafana |
We employ a continuous integration and continuous deployment (CI/CD) pipeline using Jenkins to automate the software deployment process. All code is version controlled using Git. Security updates are applied regularly following the NIST Cybersecurity Framework.
Security Considerations
Security is a paramount concern in our AI infrastructure. Several measures are in place to protect against unauthorized access and data breaches. These include:
- **Firewall:** A robust firewall protects the network from external threats.
- **Intrusion Detection System (IDS):** An IDS monitors network traffic for malicious activity.
- **Access Control:** Strict access control policies limit access to sensitive data and resources. Role-Based Access Control (RBAC) is implemented within Kubernetes.
- **Data Encryption:** Data is encrypted both in transit and at rest. We utilize TLS 1.3 for secure communication.
- **Regular Security Audits:** Regular security audits are conducted to identify and address vulnerabilities. These audits follow OWASP guidelines.
- **Vulnerability Scanning:** Automated vulnerability scanning is performed on all servers.
Future Enhancements
Planned future enhancements include:
- Upgrading to the latest generation of GPUs (NVIDIA H100).
- Implementing a distributed file system for larger datasets.
- Integrating with cloud-based AI services.
- Exploring the use of specialized AI accelerators.
- Adopting a zero-trust security model. We are currently researching Zero Trust Architecture.
AI Ethics are also being integrated into our development processes.
Server Maintenance is critical for uptime.
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.* ⚠️