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With MiningMath there is no complex and slow learning curve!

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Updated on November 18, 2024

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System requirements

The only mandatory requirement for using MiningMath is a 64-bits system. Other minimum requirements are listed further:

  1. Windows 10

  2. 64-bits system (mandatory)

  3. 110 MB of space (installation) + additional space for your projects' files.

  4. Processor: processors above 2.4 GHz are recommended to improve your experience.

  5. Memory: at least 8 GB of RAM is required. 16 GB of RAM or higher is recommended to improve your experience.

  6. Microsoft Excel.

  7. OpenGL 3.2 or above. Discover yours by downloading and running the procedure available here.

  8. Visual C++ Redistributable: Installation of Visual C++ Redistributable is necessary to run this software.

Recommended Hardware

Memory should be a higher priority when choosing the machine in which MiningMath will be run on. Here’s a list of priority upgrades to improve performance with large scale datasets: 

  1. Higher Ram

  2. Higher Ram frequency

  3. Higher processing clock

Common Issues

Insufficient memory

As previously presented, RAM should be one of the most important components to prioritize when selecting a computer to run MiningMath, especially because Windows alone consumes a significant amount of memory.

However, if you encounter an insufficient memory warning or a sudden crash while using MiningMath, there are some recommendations you can consider:

1. Memory Upgrade: If possible, this is the best solution to enhance efficiency. The characteristics to observe are listed in the previous item, “Recommended Hardware.” Based on our experience with more complex projects, 64 GB is usually sufficient for nearly all cases.

2. Free Up Memory: Consider closing other applications that are consuming the computer’s RAM while MiningMath is running.

3. Increase Windows Virtual Memory: This procedure involves allocating disk space to be used as RAM. To perform this procedure, we recommend this tutorial.

4. Reblock: If none of these options work, reblocking can be considered to reduce the size of the model. Check more details here.

Extra: In exceptional cases, when working with boxes, it may be viable to manipulate the block coordinates to bring them closer together, creating a smaller model box.

Next - Getting Started Put It to Run!
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