AI Platform
AI on Linux for AI Workloads
Run AI workloads on Linux for AI Workloads with expert guidance from Petronella
Platform-Agnostic AI Experts
24+ Years IT Infrastructure
GPU Hardware In Stock
Running AI on Linux for AI Workloads
- Recommended Distros: Ubuntu 24.04 LTS (NVIDIA DGX OS base), RHEL 9 (enterprise support), NixOS (reproducible builds), Rocky Linux 9 (free RHEL alternative)
- Gpu Support: Native CUDA, ROCm, Vulkan drivers
- Container Runtime: Docker, Podman, NVIDIA Container Toolkit
- Orchestration: Kubernetes, Slurm, Ray, NVIDIA Base Command
- Advantages: Best GPU driver support, lowest overhead, most AI frameworks native
Recommended Hardware for Linux for AI Workloads
Get the best AI performance on Linux for AI Workloads with the right GPU and system configuration.
- All NVIDIA DGX systems
- All AI servers and workstations
- RTX PRO workstations for maximum AI performance
Use Cases
- AI training and inference servers
- GPU cluster management with Slurm or Kubernetes
- Containerized AI model deployment
- NVIDIA DGX and HGX systems (all run Linux)
- Edge AI deployment on embedded Linux
- Air-gapped secure AI environments
PTG Linux for AI Workloads AI Expertise
PTG deploys and manages Linux-based AI infrastructure. Every NVIDIA DGX system runs Linux. We handle OS installation, GPU driver management, container orchestration, and security hardening for compliant AI environments.
- Platform-specific hardware recommendations
- GPU driver and framework installation
- Performance optimization and benchmarking
- Security hardening and compliance
- Ongoing management and support
Deploy AI on Linux for AI Workloads with Petronella
Our team configures and optimizes AI infrastructure for Linux for AI Workloads environments. From single workstations to enterprise clusters.