Proof of work algorithm based on random code execution. https://github.com/wownero/RandomWOW
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
tevador d40d1c149a Use a different set of round keys for AesGenerator4R 5 months ago
doc Use a different set of round keys for AesGenerator4R 5 months ago
src Use a different set of round keys for AesGenerator4R 5 months ago
vcxproj Added performance simulation 6 months ago
.gitignore Code cleanup & refactoring 6 months ago
CMakeLists.txt Correctly call JitCompiler destructor 6 months ago
LICENSE Relicensed under the 3-clause BSD license 6 months ago
README.md Minor fixes in readme 6 months ago
makefile Prepare for JIT compiler support for other platforms 6 months ago
randomx.sln Added performance simulation 6 months ago

README.md

RandomX

RandomX is a proof-of-work (PoW) algorithm that is optimized for general-purpose CPUs. RandomX uses random code execution (hence the name) together with several memory-hard techniques to minimize the efficiency advantage of specialized hardware.

Overview

RandomX behaves like a keyed hashing function: it accepts a key K and arbitrary input H and produces a 256-bit result R. Under the hood, RandomX utilizes a virtual machine that executes programs in a special instruction set that consists of a mix of integer math, floating point math and branches. These programs can be translated into the CPU’s native machine code on the fly. Example of a RandomX program translated into x86-64 assembly is program.asm. A portable interpreter mode is also provided.

RandomX can operate in two main modes with different memory requirements:

  • Fast mode - requires 2080 MiB of shared memory.
  • Light mode - requires only 256 MiB of shared memory, but runs significantly slower

Documentation

Full specification available in specs.md.

Design notes available in design.md.

Build

RandomX is written in C++11 and builds a static library with a C API provided by header file randomx.h. Minimal API usage example is provided in api-example1.c. The reference code includes a benchmark executable for testing.

Linux

Build dependencies: make and gcc (minimum version 4.8, but version 7+ is recommended).

Build using the provided makefile.

Windows

Build dependencies: Visual Studio 2017.

A solution file is provided.

Precompiled binaries

Precompiled benchmark binaries are available on the Releases page.

Proof of work

RandomX was primarily designed as a PoW algorithm for Monero. The recommended usage is following:

  • The key K is selected to be the hash of a block in the blockchain - this block is called the ‘key block’. For optimal mining and verification performance, the key should change every 2048 blocks (~2.8 days) and there should be a delay of 64 blocks (~2 hours) between the key block and the change of the key K. This can be achieved by changing the key when blockHeight % 2048 == 64 and selecting key block such that keyBlockHeight % 2048 == 0.
  • The input H is the standard hashing blob.

If you wish to use RandomX as a PoW algorithm for your cryptocurrency, we strongly recommend not using the default parameters and change at least the following:

  • Size of the Dataset (RANDOMX_DATASET_BASE_SIZE and RANDOMX_DATASET_EXTRA_SIZE).
  • Scratchpad size (RANDOMX_SCRATCHPAD_L3, RANDOMX_SCRATCHPAD_L2 and RANDOMX_SCRATCHPAD_L1).
  • Instruction frequencies (parameters starting with RANDOMX_FREQ_).

CPU mining performance

Preliminary performance of selected CPUs using the optimal number of threads (T) and large pages (if possible), in hashes per second (H/s):

|CPU|RAM|OS|AES|Fast mode|Light mode| |---|---|--|---|---------|--------------| AMD Ryzen 7 1700|16 GB DDR4|Ubuntu 16.04|hardware|4100 H/s (8T)|620 H/s (16T)| Intel Core i7-8550U|16 GB DDR4|Windows 10|hardware|1700 H/s (4T)|350 H/s (8T)| Intel Core i3-3220|2 GB DDR3|Ubuntu 16.04|software|-|145 H/s (4T)| Raspberry Pi 3|1 GB DDR2|Ubuntu 16.04|software|-|2.0 H/s (4T) †|

† Using the interpreter mode. Compiled mode is expected to increase performance by a factor of 10.

GPU mining performance

SChernykh has developed a CUDA miner for NVIDIA GPUs. Benchmarks are listed here.

Note that GPUs are at a disadvantage when running RandomX since the algorithm was designed to be efficient on CPUs.

FAQ

Does RandomX facilitate botnets/malware mining or web mining?

Efficient mining requires more than 2 GiB of memory, which is difficult to hide in an infected computer and disqualifies many low-end machines such as IoT devices. Web mining is nearly impossible due to the large memory requirement and low performance in interpreted mode.

Since RandomX uses floating point math, does it give reproducible results on different platforms?

RandomX uses only operations that are guaranteed to give correctly rounded results by the IEEE 754 standard: addition, subtraction, multiplication, division and square root. Special care is taken to avoid corner cases such as NaN values or denormals.

The reference implementation has been validated on the following platforms:

  • x86 (32-bit, little-endian)
  • x86-64 (64-bit, little-endian)
  • ARMv7+VFPv3 (32-bit, little-endian)
  • ARMv8 (64-bit, little-endian)
  • PPC64 (64-bit, big-endian)

Acknowledgements

  • SChernykh - contributed significantly to the design of RandomX
  • hyc - original idea of using random code execution for PoW
  • nioroso-x3 - provided access to PowerPC for testing purposes

RandomX uses some source code from the following 3rd party repositories:

The author of RandomX declares no competing financial interest in RandomX adoption, other than being a holder or Monero. The development of RandomX was funded from the author’s own pocket with only the help listed above.

Donations

If you’d like to use RandomX, please consider donating to help cover the development cost of the algorithm.

Author’s XMR address:

845xHUh5GvfHwc2R8DVJCE7BT2sd4YEcmjG8GNSdmeNsP5DTEjXd1CNgxTcjHjiFuthRHAoVEJjM7GyKzQKLJtbd56xbh7V