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% |
- Install Visual Studio 2017 Community and NVIDIA CUDA 10.1
- Open .sln file in Visual Studio and build it
sudo apt install build-essential git nvidia-cuda-toolkit
git clone --recursive https://github.com/SChernykh/RandomX_CUDA/
cd RandomX_CUDA
make
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