Welcome to xdagj-native-randomx

---

Introduction

xdagj-native-randomx is a Java implementation of the RandomX proof-of-work algorithm using JNA (Java Native Access). This library is a community-driven project based on the xdagj ecosystem.

What is RandomX?

RandomX is a proof-of-work (PoW) algorithm optimized for general-purpose CPUs. It uses random code execution and memory-hard techniques to minimize the efficiency advantage of specialized hardware like ASICs.

For more details, visit the RandomX GitHub repository.

---

Features

• Native Integration: Leverages RandomX's native C++ library via JNA.
• Cross-Platform Support: Works on Linux, macOS (x86_64 and aarch64), and Windows.
• Easy Integration: Available as a Maven dependency for seamless use in Java projects.

---

Donation Address

Support the project with XDAG donations:
XDAG Address: BkcVG4i1BfxUJLdNPdctaCReBoyn4j32d

---

Installation

1. Requirements

• JDK: v17 or later
• Maven: v3.9.9 or later

2. Build Steps

2.1 Clone the Repository

git clone https://github.com/XDagger/xdagj-native-randomx.git
cd xdagj-native-randomx
git submodule init
git submodule update

2.2 Compile RandomX Native Library

Compile and copy the appropriate shared library for your platform:

Linux x86_64

cd randomx
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release -DARCH=native -DBUILD_SHARED_LIBS=ON
make -j4
cp -i librandomx.so ../../src/main/resources/native/librandomx_linux_x86_64.so

macOS x86_64

cd randomx
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release -DARCH=native -DBUILD_SHARED_LIBS=ON
make -j4
cp -i librandomx.dylib ../../src/main/resources/native/librandomx_macos_x86_64.dylib

macOS aarch64

cd randomx
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release -DARCH=native -DBUILD_SHARED_LIBS=ON
make -j4
cp -i librandomx.dylib ../../src/main/resources/native/librandomx_macos_aarch64.dylib

Windows x86_64

cd randomx
mkdir build && cd build
cmake .. -G "MinGW Makefiles" -DCMAKE_BUILD_TYPE=Release -DARCH=native -DBUILD_SHARED_LIBS=ON
make -j4
cp -i randomx.dll ../../src/main/resources/native/librandomx_windows_x86_64.dll

2.3 Compile Java Library

cd ../../
mvn clean package

3. Add Maven Dependency

To include xdagj-native-randomx in your project, add the following dependency to your pom.xml:

<dependency>
    <groupId>io.xdag</groupId>
    <artifactId>xdagj-native-randomx</artifactId>
    <version>0.2.0</version>
</dependency>

---

Usage Example

package io.xdag.crypto.randomx;

import java.nio.charset.StandardCharsets;
import java.util.HexFormat;
import java.util.Set;

public class Example {
    
    public static void main(String[] args) {
        // Key to be hashed
        String key = "hello xdagj-native-randomx";
        byte[] keyBytes = key.getBytes(StandardCharsets.UTF_8);

        // Get supported RandomX flags for the current CPU
        Set<RandomXFlag> flags = RandomXUtils.getFlagsSet();
        System.out.println("Supported flags: " + flags);
        int combinedFlags = RandomXFlag.toValue(flags);
        System.out.println("Combined flags value: " + combinedFlags);

        // Initialize RandomX cache with the supported flags
        RandomXCache cache = new RandomXCache(flags);
        cache.init(keyBytes);

        // Create and configure RandomXTemplate using builder pattern
        byte[] hash;
        try (RandomXTemplate template = RandomXTemplate.builder()
                .cache(cache)
                .miningMode(false)  // Set to false for normal hashing mode
                .flags(flags)
                .build()) {

            // Initialize the template with the configured settings
            template.init();

            // Calculate hash of the input key
            hash = template.calculateHash(keyBytes);
        }

        // Format and display the results
        HexFormat hex = HexFormat.of();
        System.out.printf("Message: %s%n", key);
        System.out.printf("Hash: %s%n", hex.formatHex(hash));
    }
}

---

Benchmark Results

Linux System Configuration

• OS: Linux 5.4.119
• CPU: AMD EPYC 9754 (16 cores)
• RAM: 32 GB
• thread: 8
• RandomX Flags: [DEFAULT, HARD_AES, JIT, ARGON2_SSSE3, ARGON2_AVX2, ARGON2]

Linux Performance Results

Benchmark	Mode	Cnt	Score	Error	Units
RandomXBenchmark.lightBatch	thrpt		328.736		ops/s
RandomXBenchmark.lightNoBatch	thrpt		325.383		ops/s
RandomXBenchmark.miningBatch	thrpt		2777.939		ops/s
RandomXBenchmark.miningNoBatch	thrpt		2817.811		ops/s

---

MacOS System Configuration

• OS: macOS 15.1.1
• CPU: Apple M3 Pro
• RAM: 36 GB
• thread: 8
• RandomX Flags: [DEFAULT, HARD_AES, SECURE]

JIT flag will cause jvm to crash in MacOS

MacOS Performance Results

Benchmark	Mode	Cnt	Score	Error	Units
RandomXBenchmark.lightBatch	thrpt		32.864		ops/s
RandomXBenchmark.lightNoBatch	thrpt		33.683		ops/s
RandomXBenchmark.miningBatch	thrpt		554.966		ops/s
RandomXBenchmark.miningNoBatch	thrpt		570.060		ops/s

---

Contribution

We welcome contributions to improve the project! Please feel free to submit issues or pull requests.

For discussions or questions, contact the xdagj community.

---