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System requirements

arivis Pro is a complex software product that benefits from up-to-date hardware and software components. In the following, you find the minimum hardware and software requirements that must be met, as well as some further recommendations that guarantee an optimum user experience.

Basic requirements

These requirements define the minimum configuration needed to install, run and use arivis Pro for basic visualization and analysis.

The software is designed to process very large image datasets using tiling and temporary local storage, so the entire dataset does not need to fit into RAM. As a result, local storage and a suitable GPU are more important than very large amounts of RAM for basic operation.

Category

Requirement

Notes

Operating system
  • Microsoft Windows 11 64-bit
  • N / KN editions only work after installing the Media Feature Pack.
  • It also works with other 64bit Windows versions (e.g. Windows 10 and Windows Server).

CPU
  • 4-Core x86 compatible CPU (64-bit)

System memory (RAM)
  • 8GB RAM (minimum)
  • More RAM improves performance but is not required for basic operation.
  • arivis Pro can process datasets larger than available RAM using disk-based tilling and temporary documents.

Local storage
  • 100 GB free local disk space (minimum)
  • Local storage is used for active datasets, temporary documents and intermediate processing results.
  • Insufficient free disk space will severely limit performance and may prevent analysis.

Graphics hardware

– minimum
  • NVIDIA GPU
  • Open GL 4.6 or higher
  • 2 GB VRAM
  • Latest NVIDIA graphics driver
  • Supported example: GeForce RTX 3060 (or mobile equivalent)
  • Note: Intel and AMD GPUs may work for visualization, but are not supported. NVIDIA GPUs are strongly recommended because CUDA is required for accelerated analysis and machine learning.

– optimal
  • NVIDIA GPU
  • Open GL 4.6 or higher
  • 8 GB VRAM
  • Latest NVIDIA graphics driver
  • Supported example: GeForce RTX 4070 (or mobile equivalent)
  • Note: Intel and AMD GPUs may work for visualization, but are not supported. NVIDIA GPUs are strongly recommended because CUDA is required for accelerated analysis and machine learning.

Required software components
  • The components are installed automatically by the arivis Pro installer.

Virtual memory (page file)
  • Page file size of at least 1.5 x physical RAM
  • To ensure the smooth operation of arivis Pro, it's crucial to have a properly configured virtual memory (page file) setup, as it extends physical RAM and helps manage system resources effectively, and prevents encountering memory-related issues or crashes.

Additional requirements by feature

Additional requirements apply when using advanced features such as analysis, machine learning, deep learning and AI-assisted tools. These functions place higher demands on system memory, CPU capabilities and system configuration than basic visualization. If the corresponding requirements are not met, arivis Pro may fall back to CPU processing, which typically results in lower performance. Certain features may also not be available.

Category

Requirement

Notes

Analysis
  • 32 GB RAM (minimum)
  • 16 GB RAM per CPU core (recommended)
  • Advanced analysis operations use tiling and multithreading and therefore require more memory.
  • More memory is required to fully utilize all available CPU cores.

Machine Learning/
Deep Learning
(GPU acceleration)
  • Ensure that the GPU Support Package is selected during installation.

Deep Learning Trainer
  • NVIDIA GPU with latest driver
  • CUDA compute capabilities (version 5.2 or higher)
    see https://developer.nvidia.com/cuda-gpus whether your GPU supports it.
  • GPU that provides at least 8GB of memory (highly recommended)
  • Python 3 environment (optional installer component)

AI model store Deep Learning Segmentation
(Instance segmentation)

– Docker Desktop
(Tested successfully with version 4.56.0)
  • Windows 10 64-bit
    • Home or Pro 21H1 (build 19043) or higher
    • Enterprise or Education 20H2 (build 19042) or higher
  • Windows 11 64-bit
    • Home, Pro, Enterprise or Education version 21H2 (build 19044) or higher.
    • Recommended: 22H2 (build 19045) or higher.
  • BIOS-level Hardware Virtualization support must be enabled
  • 64 bit processor with Second Level Address Translation (SLAT)
  • WSL 2 feature on Windows (see https://docs.docker.com/desktop/wsl/)
    • Available for Windows 10 Version 1903 or higher.
    • If your version of Windows does not support: Hyper-V and Containers Windows Features must be enabled.
  • NVIDIA GPU with latest drivers supporting WSL 2 GPU Paravirtualization.
    • GPU support is only available on Windows with the WSL2 backend.
    • CUDA Compute Capability ≥ 7.0 (Volta or newer)
    • At least 8 GB CPU RAM

– Alternative setup
(If Docker Desktop or WSL2 cannot be used locally, you can use a second machine to run Docker loads remotely.)
  • Separate Linux machine (a real PC or a VM) e.g. Debian or Ubuntu
  • NVIDIA GPU (8GB RAM or higher) with CUDA Compute Capability ≥ 7.0 (Volta or newer)
  • Docker engine, configured for Docker Remote Access and NVIDIA Container Toolkit

AI-assisted mode of the Draw Tool
  • NVIDIA GPU (8GB or more recommended)
  • GPU Support Package (optional) is installed
  • Support for AI-assisted Draw Tool (optional) with additional larger AI models is highly recommended
  • Note: If these requirements are not met, calculations will default to the CPU, resulting in slower performance and reduced resolution. A smaller AI model will be used, which may decrease accuracy, especially if the GPU has less than 8GB of memory or the optional larger models are not installed.

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