AI in Iceland
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- REDIRECT AI in Iceland
AI in Iceland: Server Configuration and Infrastructure Overview
This article details the server configuration and infrastructure supporting Artificial Intelligence (AI) initiatives in Iceland. Iceland’s unique geographical advantages – abundant renewable energy, a cool climate, and reliable network connectivity – make it an increasingly attractive location for data centers and AI computation. This guide is intended for newcomers to our MediaWiki site and provides a technical overview of the core systems. We will cover hardware, networking, cooling, and power considerations. Please also review our Data Center Security Protocol and Network Topology Documentation for related information.
Hardware Infrastructure
The primary AI compute resources are housed in several geographically distributed data centers across Iceland. The choice of hardware is driven by the need for high performance, energy efficiency, and scalability. The majority of deployments utilize GPU-accelerated servers, with a growing adoption of specialized AI accelerators. See also Hardware Procurement Guidelines.
| Server Component | Specification | Quantity (approx.) |
|---|---|---|
| CPU | AMD EPYC 7763 (64-core) | 500+ |
| GPU | NVIDIA A100 (80GB) | 800+ |
| RAM | 512GB DDR4 ECC REG | 1000+ |
| Storage (Boot) | 1TB NVMe SSD | 500+ |
| Storage (Data) | 4PB NVMe SSD (RAID 0) | 20+ |
| Network Interface | 200GbE Mellanox ConnectX-6 | 1000+ |
These servers are interconnected using a high-bandwidth, low-latency network fabric, detailed in the next section. Regular hardware audits are performed, documented in the Hardware Inventory System.
Network Configuration
The network infrastructure is designed for minimal latency and maximum throughput, critical for distributed AI training and inference. The core network utilizes a Clos network topology for scalability and redundancy. We employ a combination of 100GbE and 200GbE connections, with plans to upgrade to 400GbE in the near future. Refer to the Network Bandwidth Allocation Policy for details on resource management.
| Network Component | Specification | Quantity |
|---|---|---|
| Core Routers | Cisco ASR 9912 | 4 |
| Distribution Switches | Arista 7050X | 20+ |
| Top-of-Rack Switches | Arista 7060X | 100+ |
| Interconnect Speed | 200GbE | Predominant |
| Network Protocol | TCP/IP, RDMA over Converged Ethernet (RoCEv2) | Primary |
Network monitoring is performed using Prometheus and Grafana, with alerts configured for performance degradation or outages. Detailed network diagrams are available in the Network Topology Documentation. Firewall rules are managed by the Security Operations Team.
Cooling and Power Infrastructure
Iceland's cool climate significantly reduces the energy required for cooling, making it a cost-effective location for data centers. We leverage both air cooling and direct-to-chip liquid cooling solutions. Power is sourced entirely from renewable sources – geothermal and hydroelectric. A comprehensive power redundancy system ensures uninterrupted operation. See also Power Usage Effectiveness (PUE) Monitoring.
| Infrastructure Component | Specification | Details |
|---|---|---|
| Cooling System | Direct-to-Chip Liquid Cooling & Air Cooling | Liquid cooling used for high-density GPU servers. |
| Power Source | 100% Renewable (Geothermal & Hydroelectric) | Contracted with Landsvirkjun. |
| Power Redundancy | N+1 Redundancy | Multiple independent power feeds and UPS systems. |
| PUE (Power Usage Effectiveness) | 1.15 (Average) | Continuously monitored and optimized. |
| Temperature Control | 18-22°C | Maintained within optimal operating range for hardware. |
Regular maintenance of the cooling and power systems is crucial, and is documented in the Maintenance Log. Our commitment to sustainability is outlined in the Environmental Impact Statement.
Software Stack
The primary software stack for AI development and deployment includes:
- Kubernetes: For container orchestration.
- TensorFlow: A popular machine learning framework.
- PyTorch: Another widely used machine learning framework.
- Docker: For containerization.
- Slurm: A workload manager for high-performance computing.
- Prometheus: For monitoring and alerting.
- Grafana: For data visualization.
We also provide access to various cloud-based AI services through our Cloud Services Portal. Detailed software installation guides are available on the Software Repository.
Future Expansion
We are continuously expanding our AI infrastructure to meet growing demand. Planned upgrades include:
- Deployment of next-generation GPUs (NVIDIA H100).
- Expansion of the network to 400GbE.
- Increased liquid cooling capacity.
- Exploration of new AI accelerator technologies.
These future developments are tracked in the Capacity Planning Document. Please consult the Change Management Process before implementing any changes to the infrastructure.
Data Center Security Protocol
Network Topology Documentation
Hardware Procurement Guidelines
Hardware Inventory System
Network Bandwidth Allocation Policy
Security Operations Team
Power Usage Effectiveness (PUE) Monitoring
Maintenance Log
Environmental Impact Statement
Kubernetes
TensorFlow
PyTorch
Docker
Slurm
Cloud Services Portal
Software Repository
Capacity Planning Document
Change Management Process
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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.* ⚠️