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Data Center

Data Center Infrastructure and Computational Resources Overview

Exo Power Computing operates a network of high performance computing facilities across European and UK locations, designed to support intensive computational workloads with an emphasis on artificial intelligence applications. The infrastructure implements distributed computing architecture with redundant systems to ensure operational continuity.

The computational infrastructure comprises multiple processing clusters, each equipped with GPU accelerators optimized for parallel processing and matrix operations common in machine learning workloads. The systems support standard machine learning frameworks and CUDA acceleration, enabling compatibility with established development environments and toolchains.

The network topology implements high-bandwidth, low-latency connections between computing nodes, with measured latency typically remaining under 2ms within each facility. Inter facility communication utilizes dedicated fiber optic links to maintain consistent performance across geographical locations. The infrastructure supports both batch processing and real-time inference workloads through automated resource allocation and load balancing.

Cooling systems employ a combination of free air cooling and liquid cooling solutions, with heat exchangers operating at a Power Usage Effectiveness (PUE) ratio of 1.2 to 1.3 depending on location and seasonal variations. Power distribution systems implement N+1 redundancy with uninterruptible power supplies and diesel generators providing backup power capacity for 72 hours of continuous operation.

The facilities maintain ISO 27001 certification for information security management and comply with relevant data protection regulations including GDPR. Access control systems implement multi factor authentication and maintain detailed audit logs of all physical and digital access events.

Resource allocation follows a containerized approach, enabling dynamic scaling of computational resources based on workload requirements. The infrastructure supports various deployment models, from dedicated bare metal installations to virtualized environments, allowing for flexibility in resource utilization.

The power infrastructure incorporates renewable energy sources where available, with facilities maintaining power purchase agreements with wind and solar generators. Energy monitoring systems provide real time metrics on power consumption and efficiency, enabling optimization of resource allocation based on energy availability and cost.

Current expansion plans focus on increasing computational density through the integration of next generation processing units and improved cooling systems. The infrastructure roadmap includes provisions for quantum computing integration as the technology matures and becomes commercially viable.

Research institutions, government agencies, and commercial organizations can access these computational resources through standardized APIs and management interfaces. The system architecture supports both shared and isolated computing environments to accommodate varying security and performance requirements.

Last updated 5 months ago

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