Overview
x86 Platform with GPU Cards
About Advantech Container Catalog
Advantech Container Catalog is a comprehensive collection of ready-to-use, containerized software packages designed to accelerate the development and deployment of Edge AI applications. By offering pre-integrated solutions optimized for embedded hardware, it simplifies the challenges often faced with software and hardware compatibility, especially in GPU/NPU-accelerated environments.
Key benefits of the Container Catalog include:
| Feature / Benefit | Description |
|---|---|
| Accelerated Edge AI Development | Ready-to-use containerized solutions for fast prototyping and deployment |
| Hardware Compatibility Solved | Eliminates embedded hardware and AI software package incompatibility |
| GPU/NPU Access Ready | Supports passthrough for efficient hardware acceleration |
| Model Conversion & Optimization | Built-in AI model quantization and format conversion support |
| Optimized for CV & LLM Applications | Pre-optimized containers for computer vision and large language models |
| Scalable Device Management | Supports large-scale IoT deployments via EdgeSync, Kubernetes, etc. |
| Lower Entry Barrier for Developers | High-level language (Python, C#, etc.) support enables easier development |
| Developer Accessibility | Junior engineers can build embedded AI applications more easily |
| Increased Customer Stickiness | Simplified tools lead to higher adoption and retention |
| Open Ecosystem | 3rd-party developers can integrate new apps to expand the platform |
Container Overview
x86 Platform with GPU Card container is a base image that provides a pre-configured development environment with GPU passthrough capabilities, designed for industrial AI and machine learning applications. This solution simplifies the deployment of GPU-accelerated workloads in edge computing environments while ensuring consistent, reproducible results across development and production environments.
Key Features
Optimized for AI development on GPU, this container provides full GPU passthrough, and essential tools pre-installed for rapid deployment.
| Feature | Content |
|---|---|
| Automatic GPU Toolkit Detection | Automatically detects installed GPU Toolkit version from your system |
| Flexible Configuration | Supports command-line configuration of CUDA Toolkit and versions |
| Complete GPU Passthrough | Utilizes GPUs with full compute capabilities |
| Optimized Memory Management | Configured with 8GB shared memory for high-performance GPU operations |
| Pre-installed Development Tools | Ubuntu 22.04 LTS base with essential development packages |
Application Support
The Advantech x86 Platform with GPU Card container is tailored for high-performance AI and ML workloads. It supports a wide range of frameworks and libraries optimized for GPU acceleration in edge and industrial environments:
| Application | Content |
|---|---|
| Deep Learning Frameworks | TensorFlow, PyTorch, JAX, MXNet |
| Computer Vision Libraries | OpenCV and more |
| HPC Applications | GPU-accelerated scientific computing |
| Data Science | NumPy, SciPy, scikit-learn with GPU acceleration |
| NLP Processing | BERT, GPT, and transformer models |
| Industrial Applications | Edge AI, Computer Vision, Predictive Maintenance |
Host Device Prerequisites
Users should ensure that the selected Advantech host device meets the specifications below and has the required software packages installed before running this container image.
| Item | Specification |
|---|---|
| Compatible Hardware | Advantech x86 Edge Devices (tested on AIR-520) - refer to Compatible hardware |
| Docker & Docker Compose | both versions > 2.0 |
| Recommended Device OS | Linux-based operating system (Ubuntu 20.04+) |
| SUSI IoT Installation | SUSI drivers installed on host system SUSI IoT Installation Guide |
For more detailed Software Installation, please refer to : x86 Platform with GPU Card Container Repository
Validated Hardware Platform
The x86 Platform with GPU Card has been thoroughly tested and validated on Advantech AIR-520 with detailed hardware specification below:
Container Environment Overview
Pre-installed Development Tools on Container Image
The x86 Platform with GPU Card container comes with these essential development tools pre-installed:
| Type | Components |
|---|---|
| Build Tools | gcc/g++, make, cmake, build-essential |
| Version Control | git |
| Python Environmen | Python 3 with pip |
| Utilities | wget, curl, vim, unzip |
| System Tools | ca-certificates, gnupg2, lsb-release, software-properties-common |
GPU Passthrough Capabilities
The Advantech L2-01 container supports full GPU passthrough for:
The container can handle:
- Up to 8 GPUs simultaneously
- Up to 96GB VRAM per GPU
- Mixed GPU types in the same system
- Dynamic GPU allocation
For more details, please refer to : x86 Platform with GPU Card Container Repository
Container Quick Start Guide
For container quick start, including docker-compose file, and more, please refer to Advantech EdgeSync Container Repository