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RandomX CUDA implementation

This repository contains full RandomX implementation for NVIDIA GPUs. The latest version of RandomX (1.1.0 as of August 30th, 2019) is supported.

Note: it's only a benchmark/testing tool, not an actual miner. RandomX hashrate is expected to improve somewhat in the future thanks to further optimizations.

GPUs tested so far:

Model CryptonightR H/S RandomX H/S Relative speed
GTX 1050 2GB (stock) 299 (75 W) 181 (75 W) 60.5%
GTX 1660 Ti max overclock (2070/13760 MHz) 626 (98 W) 671 (103 W) 107.2%
GTX 1660 Ti low power (1785/13760 MHz) 604 (70 W) 567 (70 W) 93.9%
GTX 1070 (1850/7600 MHz) [1] 612 (89 W) 609 (108 W) 99.5%
GTX 1070 Ti (1900/7600 MHz) [2] 625 (97 W) 769 (123 W) 123.0%
GTX 1080 Ti (1930/10010 MHz)[3] 787 (145 W) 1136 (190 W) 144.3%
GTX 1080 Ti (2037/11800 MHz) 927 (183 W) 1122 (190 W) 121.0%
RTX 2080 (1980/13740 MHz) [4] 828 (142 W) 1191 (189 W) 143.8%
RTX 2080 Ti (1915/13600 MHz) [5] 1105 (197 W) 1641 (242 W) 148.5%
Titan V (1335/850 MHz) [6] 1436 (101 W) 2199 (125 W) 153.1%
Tesla V100 (1530/877 MHz) [7] 1798 (134 W) 2524 (177 W) 140.4%

Building on Windows

  • Install Visual Studio 2017 Community and NVIDIA CUDA 10.1
  • Open .sln file in Visual Studio and build it

Building on Ubuntu

sudo apt install build-essential git nvidia-cuda-toolkit
git clone --recursive https://github.com/SChernykh/RandomX_CUDA/
cd RandomX_CUDA
make

Donations

If you'd like to support further development/optimization of RandomX miners (both CPU and AMD/NVIDIA), you're welcome to send any amount of XMR to the following address:

44MnN1f3Eto8DZYUWuE5XZNUtE3vcRzt2j6PzqWpPau34e6Cf4fAxt6X2MBmrm6F9YMEiMNjN6W4Shn4pLcfNAja621jwyg

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RandomX CUDA implementation

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