AI Framework

ROCm

By AMD

Local AI Deployment Experts 24+ Years IT Infrastructure Enterprise-Ready Solutions

What ROCm Does

  • Type: Open-source GPU compute platform (AMD alternative to CUDA)
  • Version: ROCm 6.x
  • Supported Gpus: AMD Instinct MI300X, MI250X, Radeon PRO W7900, RX 7900 XTX
  • Frameworks: PyTorch (native), TensorFlow, ONNX Runtime, vLLM
  • Api: HIP (CUDA-compatible API), OpenCL, Vulkan compute

Use Cases

  • AI training and inference on AMD GPUs
  • Cost-effective alternative to NVIDIA CUDA ecosystem
  • Open-source GPU compute for transparency requirements
  • Mixed AMD/NVIDIA GPU environments
  • HPC workloads on AMD Instinct accelerators
  • Research requiring open-source GPU toolchains

Recommended Hardware

Get the best performance from ROCm with the right infrastructure.

  • AMD Instinct MI300X (192GB HBM3)
  • AMD Instinct MI250X (128GB HBM2e)
  • AMD Radeon AI PRO R9700 (32GB)

Deploy ROCm with Petronella

PTG configures ROCm for organizations using AMD GPUs for AI. We optimize PyTorch, vLLM, and other frameworks for AMD Instinct and Radeon PRO hardware, providing a cost-effective CUDA alternative.

  • Hardware procurement and configuration
  • Production deployment and optimization
  • Ongoing monitoring and support
  • Security hardening and compliance

Need Help Deploying ROCm?

Our infrastructure team can design, build, and support your ROCm deployment from day one.

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