AI in Puerto Rico
AI in Puerto Rico: Server Configuration and Deployment Considerations
This article details the server configuration considerations for deploying Artificial Intelligence (AI) workloads in Puerto Rico. It is geared towards newcomers to our MediaWiki site and aims to provide a technical overview of hardware, software, and infrastructure challenges unique to the region. This document assumes a baseline understanding of server administration and networking principles. See Special:MyPage for more information about the author.
Introduction
Puerto Rico presents a unique set of challenges and opportunities for AI deployment. Factors such as power grid stability, internet connectivity, and geographic vulnerabilities (hurricanes, earthquakes) require careful planning. This document outlines a robust server configuration strategy to address these concerns. Successful AI implementation relies on a strong foundation of reliable hardware and optimized software. Refer to Help:Contents for general wiki help. Contact User:Admin for further assistance.
Hardware Infrastructure
Choosing the right hardware is critical. Given the potential for power disruptions, redundancy and energy efficiency are paramount. We focus on a hybrid approach utilizing both on-premise and cloud resources, leveraging the strengths of each.
| Component | Specification | Quantity | Estimated Cost (USD) |
|---|---|---|---|
| CPU | AMD EPYC 7763 (64 Core) | 4 | $8,000 |
| RAM | 512GB DDR4 ECC Registered | 4 | $4,000 |
| Storage (Primary) | 2TB NVMe SSD (RAID 1) | 4 | $2,000 |
| Storage (Secondary) | 16TB HDD (RAID 6) | 2 | $1,000 |
| GPU | NVIDIA A100 (80GB) | 2 | $20,000 |
| Network Interface | 100GbE Network Card | 2 | $1,000 |
| Power Supply | 2000W Redundant Power Supply | 2 | $800 |
This table represents the core specifications for a single on-premise server. Multiple servers would be deployed in a clustered configuration for high availability. See Help:Tables for details on table formatting. Consider Help:Linking for internal links.
Software Stack
The software stack should focus on scalability, containerization, and ease of management. We recommend a Linux-based operating system, specifically Ubuntu Server 22.04 LTS.
| Software | Version | Purpose |
|---|---|---|
| Operating System | Ubuntu Server 22.04 LTS | Base Operating System |
| Containerization | Docker 24.0.5 | Application Packaging and Deployment |
| Orchestration | Kubernetes 1.28 | Container Management and Scaling |
| AI Framework | TensorFlow 2.13.0 / PyTorch 2.0.1 | Machine Learning Development |
| Database | PostgreSQL 15 | Data Storage and Management |
| Monitoring | Prometheus & Grafana | System Monitoring and Alerting |
Using containerization and orchestration allows for easy deployment and scaling of AI models. Refer to Help:Editing for detailed editing instructions. The choice between TensorFlow and PyTorch depends on the specific AI application. Understanding Help:Formatting is vital.
Network and Connectivity Considerations
Puerto Rico's internet infrastructure can be unreliable. A redundant network configuration is crucial. This includes multiple internet service providers (ISPs) and a robust local network.
| Network Component | Specification | Quantity | Notes |
|---|---|---|---|
| Internet Connection 1 | 100 Mbps Dedicated Fiber | 1 | Primary ISP |
| Internet Connection 2 | 50 Mbps Wireless Backup | 1 | Secondary ISP - for failover |
| Router/Firewall | Cisco ASA 5516-X | 1 | Network Security and Management |
| Switch | Cisco Catalyst 9300 Series | 1 | Core Network Switch |
| VPN | OpenVPN | 1 | Secure Remote Access |
A Virtual Private Network (VPN) is essential for secure remote access to the servers. Load balancing should be implemented to distribute traffic across multiple servers. See Help:Search for finding information. Consider using a Content Delivery Network (CDN) for distributing AI model outputs. Power redundancy is critical, and a UPS system is mandatory, see Help:Advanced Topics.
Power Management and Redundancy
Given the history of power outages in Puerto Rico, a comprehensive power management strategy is vital. This includes:
- **UPS Systems:** Uninterruptible Power Supplies (UPS) for all servers and network equipment.
- **Generators:** Backup generators with sufficient capacity to power the entire server infrastructure for an extended period.
- **Power Conditioning:** Voltage stabilizers and surge protectors to protect against power fluctuations.
- **Energy Efficiency:** Choosing energy-efficient hardware and optimizing software to reduce power consumption.
Disaster Recovery
A robust disaster recovery plan is essential. This includes regular backups to offsite locations (cloud storage is ideal) and a documented procedure for restoring services in the event of a natural disaster. Automated backups are highly recommended. Review Help:Page history to track changes.
Conclusion
Deploying AI in Puerto Rico requires careful consideration of the unique challenges presented by the region. A robust server configuration, coupled with a comprehensive disaster recovery plan, is essential for success. This article provides a starting point for planning an AI infrastructure in Puerto Rico. Always consult with local experts and tailor the configuration to your specific needs. Refer to Help:About Wiki for information about the wiki itself.
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.* ⚠️