NovaNet Validator Setup on NVIDIA Jetson Orin Nano

NovaNet Validator Setup on NVIDIA Jetson Orin Nano

Introduction

NovaNet is a quantum-secure, AI-optimized blockchain that leverages NVIDIA Jetson Orin Nano for high-performance validator operations.

This guide provides step-by-step instructions to:

• Deploy a NovaNet Validator Node
• Enable GPU acceleration using NVIDIA TensorRT
• Integrate AI-based validator selection
• Optimize validator performance with TensorRT-accelerated models

🔗 NovaNet Validator GitHub Repository

---

1. Prerequisites

Before deploying a NovaNet Validator on Jetson Orin Nano, ensure you have:

• Jetson Orin Nano Developer Kit
• Ubuntu 20.04 (L4T) with NVIDIA JetPack SDK installed
• Minimum 16GB microSD card or NVMe SSD for storage
• Internet connection for package installation

---

2. Install Dependencies on Jetson Orin Nano

Update the system and install required dependencies:

sudo apt update && sudo apt upgrade -y
sudo apt install -y build-essential git cmake curl jq \
    python3-pip libssl-dev nvidia-jetpack cuda-toolkit-10-2 \
    libcudnn8 tensorrt libnvinfer7 libnvinfer-plugin7

---

3. Clone the NovaNet Validator Repository

git clone https://github.com/Galactic-Code-Developers/NovaNet-Validator.git
cd NovaNet-Validator

---

4. Build and Compile NovaNet Validator

make build

---

5. Install NVIDIA TensorRT and Optimize Validator Execution

5.1 Install TensorRT Python Bindings

pip3 install pycuda
pip3 install tensorrt

5.2 Optimize NovaNet Validator with TensorRT

We use TensorRT-optimized AI models to enhance validator selection and boost performance.

Create a TensorRT model loader (validator_inference.py):

import tensorrt as trt
import pycuda.driver as cuda
import pycuda.autoinit

def load_engine(trt_file_path):
    with open(trt_file_path, "rb") as f:
        runtime = trt.Runtime(trt.Logger(trt.Logger.WARNING))
        return runtime.deserialize_cuda_engine(f.read())

engine = load_engine("validator_model.trt")

def select_validator(input_data):
    context = engine.create_execution_context()
    output = context.execute_v2(bindings=[input_data])
    return output

• This enables TensorRT acceleration for validator selection.

---

6. Modify NovaNet Validator Code to Use GPU

6.1 Update NovaNet Validator to Use AI-Based Selection

Modify the NovaNet Validator script to integrate TensorRT AI acceleration:

Edit novanet-cli (or relevant execution script):

from validator_inference import select_validator

def run_validator():
    validator_data = load_validator_data()
    best_validator = select_validator(validator_data)
    print(f"Selected Validator: {best_validator}")

• This ensures AI-based validator selection using TensorRT inference.

---

7. Deploy NovaNet Validator Using Docker

We use a custom NVIDIA Jetson-optimized Dockerfile:

Create Dockerfile:

# Use NVIDIA’s CUDA-enabled base image for Jetson devices
FROM nvcr.io/nvidia/l4t-base:r32.7.1

# Set working directory
WORKDIR /novanet

# Install dependencies and Jetson SDK
RUN apt update && apt install -y \
    build-essential git cmake curl jq python3-pip libssl-dev \
    nvidia-jetpack cuda-toolkit-10-2 libcudnn8 tensorrt libnvinfer7 libnvinfer-plugin7 \
    && rm -rf /var/lib/apt/lists/*

# Set environment variables for CUDA and TensorRT
ENV PATH=/usr/local/cuda/bin:$PATH
ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH

# Copy NovaNet validator source code
COPY . /novanet

# Build the validator
RUN make build

# Start the NovaNet validator with GPU acceleration
CMD ["novanet-cli", "start", "--validator", "--use-gpu"]

---

8. Run the NovaNet Validator with GPU Acceleration

Use Docker to run the validator:

docker build -t novanet-validator 
docker run --runtime nvidia --gpus all -d novanet-validator

• This ensures the validator is fully optimized for Jetson Orin Nano.

---

9. Monitor Validator Performance

To check the validator logs and AI inference execution:

docker logs -f novanet-validator

• This will display AI-driven validator selection and network participation.

---

10. How to Contribute

NovaNet Validator is open-source, and we welcome contributions! You can help by:

• Forking the repository and submitting pull requests.
• Improving validator performance optimizations.
• Developing new AI-powered selection algorithms.

🚀 Start contributing: 🔗 NovaNet Validator GitHub Repository

📚 Additional Resources

🔗 NovaNet Whitepaper
🔗 Glossary of Terms
🔗 Consensus Mechanism Overview

---

11. Join the NovaNet Community

📢 Follow NovaNet for updates: 💬 Discord: Join Discussion
📢 Twitter: @NovaNet_Official
👨‍💻 Telegram: Community Chat

---

• NovaNet Validator on Jetson Orin Nano ensures high-performance, AI-driven blockchain validation with NVIDIA GPU acceleration!

---

🌍 The Future of Quantum Blockchain Starts Here!
Welcome to NovaNet – A Scalable, Secure, and Quantum-Optimized Future!