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MinAXNT

MinAXNT is a Go implementation of the Axentro mining protocol.

You can find more information about Axentro on the website: https://axentro.io/.

MinAXNT is well tested on:

  • GNU/Linux
    • x86_64
    • ARM aarch64 (Raspberry Pi 3 Rev.3, Android smartphone with Termux)
  • MacOS (x86_64)
  • Windows
    • x86_64

Install

Installing MinAXNT is really simple:

First: You need an Axentro wallet address to start mining, please visite the website or the Youtube channel

You can create a wallet with the Web wallet

Usage

./minaxnt -n http://mainnet.axentro.io -a TTBjMjg1NWJmZTIwMTA3MDc3NTZkNjg1MTcxYjE1YmE5ZjU3N2EzODhkYWRiZWIy -p 2

OR

./minaxnt --node http://mainnet.axentro.io --address TTBjMjg1NWJmZTIwMTA3MDc3NTZkNjg1MTcxYjE1YmE5ZjU3N2EzODhkYWRiZWIy --process 2

OR

minaxnt.exe --node http://mainnet.axentro.io --address TTBjMjg1NWJmZTIwMTA3MDc3NTZkNjg1MTcxYjE1YmE5ZjU3N2EzODhkYWRiZWIy --process 2

Have fun !

Tunning

CPU Affinity : Hyper-Threaded Architecture

Sometime you have to use the same computer for mining and doing other stuff at the same time.

That's interesting to configure MinAXNT to use only a limited cores in order to use your computer in the same time.

To use MinAXNT on only 4 cores (the most powerful) go to the section corresponding to your use case:

Linux with taskset

On linux the most powerful cores in HT CPU are those who have an even index (0, 2, 4, 6, 8, 10, ...).

Most distribution have taskset binary.

taskset -c 0,2,4,6 ./minaxnt -a TTBjMjg1NWJmZTIwMTA3MDc3NTZkNjg1MTcxYjE1YmE5ZjU3N2EzODhkYWRiZWIy -n http://localhost:3000 -p4

This way only 4 cores are used for MinAXNT and the others for other stuff like programming, gaming or Internet, ...

Windows [WIP]

On Windows the most powerful cores in HT CPU are those who have an odd index (1, 3, 5, 7, 9, 11, ...).

Device Performance (Argon2id)

Device Type CPU Model Operating System MinAXNT process param Work/s MinAXNT version
iMac Pro Desktop Intel Xeon W-?? @3.00 GHz 10-core 64-bit MacOs Catalina 40 160.0 Work/s v0.7.0
MacBook Pro Laptop Intel Core i9-?? [email protected] GHz 8-Core 64-bit MacOS Big sur 30 108.0 Work/s v0.7.0
MinisForum: DMAF5 Mini-PC AMD Ryzen 5 3550H with Radeon Vega Mobile Gfx @2.10 GHz 4-core HT (8 vcore) 64-bit Windows 10 Family (x86_64) 8 69.0 Work/s v0.9.0
Lenovo: Y510P Laptop Intel(R) Core(TM) i7-4700MQ @2.40GHz Rev.3 4-core HT (8 vcore) 32-bit-64-bit Ununtu 18.04 (x86_64) 8 49.0 Work/s (45 Work/s when using only the 4 physical CPU: taskset -c 0,2,4,6 ./minaxnt -a xxx -p4) v0.9.0
IMB/PC Laptop Intel i7-7820 HQ @2.90 GHz 4-core HT (8 vcore) 64-bit Windows 10 Pro ?? 36.0 Work/s v0.7.0
IBM/PC Desktop Intel(R) Celeron(R) CPU G3900 @ 2.80GHz 2-core 64-bit Ubuntu 18.04 (aarch64) 3 24.8 Work/s v0.10.0
Xiaomi MI 6 Smartphone Qualcomm Snapdragon 835: 4x Kryo 280 @2.45 GHz, 4x Kryo 280 @1.9 GHz (Octa-core, Cortex A72 or A73) Android 9 8 15.7 Work/s v0.10.0
PINE64: ROCKPro64 2Gio RAM SBC (ARM) RK3399 Hexa-Core (2x ARM Cortex A72, 2.0GHz + 4x ARM Cortex A53, 1.5GHz) Ubuntu 18.04 (aarch64) 6 10.0 Work/s v0.7.0
Samsung Galaxy A7 Smartphone 2 x Cortex-A73 + 6 Cortex-A53 - @2.2 GHz Android 10 2 7.0 Work/s v0.10.0
Raspberry Pi 4, ?? Gio RAM SBC (ARM) 4x ARM Cortex-A72, 1.5GHz ?? (aarch64) ?? xx.x Work/s -
Raspberry Pi 3 Model B Rev 1.2, 1 Gio RAM SBC (ARM) 4x ARM Cortex-A53, 1.2GHz Alpine Linux 5.4.84-0-rpi (aarch64) 4 2.6 Work/s v0.9.0

License

This project is under the MIT License. See the LICENSE file for the full license text.