dGB Earth Sciences
    Software

    System Requirements

    Hardware and software specifications for running OpendTect on Windows, Linux, and Cloud.

    View supported platforms by product →

    Minimum

    VersionWindows 10/11. Older Windows versions are not officially supported, but may work.
    CPUIntel/AMD, 64-bit.
    GPUBasic Intel graphics or Nvidia (recent GeForce/Quadro/NVS series); AMD graphics cards may work.
    MemoryDDR4 memory, 16 GB of RAM. OpendTect itself needs at least 2 GB RAM, so 16 GB is the absolute minimum.
    StorageHard Disk.

    Recommended

    VersionWindows 10/11. Older Windows versions are not officially supported, but may work.
    CPUIntel/AMD 64-bit, 3+ GHz multi-core. OpendTect uses all available cores; the more cores and speed, the better.
    GPUNvidia main-stream to high-end GeForce; Quadro or NVS may give extra performance. For laptops, ensure an Nvidia chipset.
    MemoryDDR4 or DDR5, no less than 32 GB. Large clients use 512 GB or more — buy as much as you can afford.
    StorageSSD is best; Hard Disk and Network Drive also work. SSDs give a major performance boost — slow disks/networks can cripple performance.

    For Machine Learning

    VersionWindows 10/11. Older Windows versions are not officially supported, but may work.
    CPUIntel 64-bit for the Intel MKL (CPU-only) Python environment. AMD 64-bit is fine for the CUDA 11.3 GPU Python environment. Ideally expandable to 4 GPUs — at least 8 cores, 16 threads and 40 PCIe lanes recommended.
    GPUNvidia GeForce or Quadro. Choose for memory size, CUDA cores, tensor cores and memory bandwidth. Recommended: Turing (RTX 2080 Ti, Quadro RTX 6000/8000), Ampere (RTX 3080 Ti, RTX 3090, A40), Ada Lovelace (RTX 4070 Ti, RTX 4080, RTX 4090).
    MemoryDDR4 or DDR5, no less than 32 GB. Buy as much as you can afford.
    StorageM.2 NVMe SSD is best — plugged directly into the motherboard and very fast. SATA SSD, Hard Disk and Network Drive are alternatives.

    Please note that…

    • For best performance OpenGL drivers should be up-to-date. For Machine Learning on GPU we provide a Python package with CUDA 11.3.
    • The CUDA 10 Python environment is obsolete and will no longer receive security updates — replace it with CUDA 11 or use the CPU-only environment.
    • 4K/8K screens are not fully supported yet, depending on scaling factor.
    • Windows needs to be kept up to date with the latest Microsoft updates.