AI in France
- AI in France: A Server Configuration Overview
This article details the server infrastructure supporting Artificial Intelligence (AI) initiatives within France. It's designed for newcomers to our MediaWiki platform and provides a technical overview of the hardware and software configurations employed. Understanding this setup is crucial for contributing to projects relying on these resources, and for those involved in system administration or data science tasks.
Overview
France has significantly invested in AI development, requiring robust and scalable server infrastructure. This infrastructure is distributed across several key regions, including Paris, Lyon, and Toulouse, to ensure redundancy and proximity to research institutions and industry partners. The core philosophy centers around utilizing a hybrid cloud approach, combining on-premise high-performance computing (HPC) clusters with public cloud services from providers like OVHcloud and Amazon Web Services. This allows for flexibility, cost efficiency, and access to cutting-edge technologies. We leverage containerization via Docker and orchestration via Kubernetes extensively.
Hardware Specifications
The on-premise clusters primarily utilize high-density server racks equipped with the following specifications.
| Component | Specification | Quantity (Typical Rack) |
|---|---|---|
| CPU | Dual Intel Xeon Platinum 8380 | 2 |
| RAM | 512 GB DDR4 ECC Registered | 1 |
| GPU | 8 x NVIDIA A100 80GB | 1 |
| Storage | 2 x 8 TB NVMe SSD (RAID 1) | 1 |
| Network Interface | Dual 200 Gbps InfiniBand | 1 |
These racks are interconnected using a high-bandwidth, low-latency InfiniBand network, crucial for distributed training of large AI models. Currently, we maintain approximately 50 of these racks across our primary data centers. Network Topology documentation is available on the Internal Documentation page.
Software Stack
The software stack is built around a core Linux distribution, primarily Ubuntu Server 22.04 LTS. We employ a layered approach, starting with the operating system and building up to the AI frameworks.
| Layer | Software | Version |
|---|---|---|
| Operating System | Ubuntu Server | 22.04 LTS |
| Containerization | Docker | 24.0.5 |
| Orchestration | Kubernetes | 1.27 |
| AI Frameworks | TensorFlow, PyTorch, JAX | Latest Stable Releases |
| Data Management | PostgreSQL, Hadoop, Spark | Latest Stable Releases |
All code is version controlled using Git and hosted on our internal GitLab instance. Automated deployment pipelines are managed by Jenkins. We also utilize Prometheus and Grafana for monitoring system performance and identifying potential bottlenecks. Detailed instructions for setting up a development environment are available on the Developer Guide.
Cloud Integration Details
Our hybrid cloud strategy incorporates both OVHcloud and AWS. OVHcloud provides cost-effective virtual machine instances for less demanding workloads, while AWS is leveraged for specialized services like SageMaker and access to a wider range of AI/ML tools.
| Cloud Provider | Service | Typical Use Case |
|---|---|---|
| OVHcloud | Public Cloud Instances (various sizes) | Batch processing, data storage, web applications |
| Amazon Web Services | SageMaker | Model training and deployment |
| Amazon Web Services | S3 | Long-term data archiving |
| Amazon Web Services | EC2 | Burst capacity during peak demand |
Data transfer between on-premise clusters and cloud providers is secured using VPN connections and encrypted storage. Strict data governance policies are enforced to ensure compliance with French and European regulations. Details on accessing cloud resources can be found in the Cloud Access Guide.
Future Expansion
Future plans include expanding HPC capabilities with the introduction of new servers utilizing the latest generation of GPUs (e.g., NVIDIA H100). We are also investigating the use of quantum computing resources for specific AI applications. Furthermore, we are actively researching and implementing federated learning techniques to enable collaborative AI development while preserving data privacy. The Roadmap document details the projected timeline for these upgrades.
Internal Documentation System Administration Data Science Paris Lyon Toulouse OVHcloud Amazon Web Services Docker Kubernetes Ubuntu Server Git GitLab Jenkins Prometheus Grafana Network Topology Developer Guide Cloud Access Guide Data Governance Roadmap Quantum Computing Federated Learning PostgreSQL Hadoop Spark SageMaker
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.* ⚠️