GPU-Powered AI/ML Infrastructure

Xelon provides enterprise-grade NVIDIA GPU infrastructure optimized for AI/ML workloads. Train large language models, run computer vision pipelines, or accelerate scientific simulations on Swiss infrastructure with zero egress fees.

Available GPU Hardware:

• NVIDIA A100 80GB: 6912 CUDA cores, 432 Tensor cores, 312 TFLOPS FP16 (CHF 2.50/hour)

• NVIDIA H100 80GB: 16896 CUDA cores, 989 TFLOPS FP16, 3x faster LLM training (CHF 4.00/hour)

• Multi-GPU Configurations: 1-8 GPUs per server with NVLink interconnect

• InfiniBand Networking: 100 Gbps HDR for distributed training clusters

Pre-Installed AI/ML Stack:

• Deep Learning Frameworks: PyTorch 2.2, TensorFlow 2.15, JAX 0.4.23, MXNet

• CUDA Toolkit: CUDA 12.3, cuDNN 8.9, NCCL for multi-GPU communication

• Model Serving: vLLM, TensorRT-LLM, Triton Inference Server for production inference

• Jupyter Notebooks: JupyterLab with GPU-enabled kernels for experimentation

Cost Comparison (A100 80GB on-demand):**

• AWS p4d.24xlarge (8x A100): CHF 32.77/hour = CHF 23,594/month

• Google Cloud A2 Ultra (8x A100): CHF 28.50/hour = CHF 20,520/month

• Xelon (8x A100 80GB): CHF 20.00/hour = CHF 14,400/month ✅ (39% cheaper)

Use Cases:

• LLM Training: Fine-tune GPT, LLaMA, Mistral models with DeepSpeed or FSDP

• Computer Vision: Object detection (YOLOv8), image segmentation, Stable Diffusion

• Scientific Computing: Molecular dynamics (GROMACS), CFD (OpenFOAM), genomics

• Inference: Real-time model serving for production applications

Swiss AI Advantage:

• Zero Egress Fees: Download trained models and datasets without bandwidth charges

• Data Privacy: Train on sensitive data with Swiss data residency and GDPR compliance

• Research Grants: Eligible for Swiss National Science Foundation (SNSF) compute funding