DGX Music - AI-Powered Music Production Platform
Production-grade AI music generation and editing system for NVIDIA DGX Spark
Overview
DGX Music is a comprehensive AI-powered music production platform that brings cutting-edge music generation capabilities to professional DAW workflows. Built specifically for NVIDIA DGX Spark hardware, this system combines state-of-the-art open source AI models with traditional music production tools to enable natural language music creation, real-time editing, and professional-quality output.
Key Capabilities
- Full Song Generation: Generate complete songs with vocals and accompaniment using YuE and DiffRhythm models
- Genre-Specific Training: Fine-tuned models for hip-hop and EDM/dubstep production
- DAW Integration: Seamless integration with Ardour DAW via MCP (Model Context Protocol)
- Text-to-Music Pipeline: Natural language prompts → MIDI → rendered audio
- Real-Time Editing: Edit generated music with professional plugins and virtual instruments
- Production Architecture: Scalable Kubernetes deployment with 110GB memory optimization
Target Hardware
- Platform: NVIDIA DGX Spark
- Memory: 128GB unified LPDDR5x
- GPU: NVIDIA GB10 Grace Blackwell Superchip
- CPU: 20-core ARM (10x Cortex-X925 + 10x Cortex-A725)
- Storage: 4TB SSD
Quick Start
# Clone the repository
git clone https://github.com/[your-org]/dgx-music.git
cd dgx-music
# Run initialization
just init
# Start services
tilt upArchitecture
┌─────────────────────────────────────────────────────────────┐
│ ARDOUR DAW │
│ Professional music editing │
└─────────┬────────────────────────────┬─────────────────────┘
│ │
┌─────▼─────────┐ ┌──────▼──────────┐
│ AI Generation│ │ Audio Rendering │
│ - YuE │ │ - FluidSynth │
│ - DiffRhythm │ │ - Carla Host │
│ - MusicGen │ │ - VST/LV2 │
└───────┬───────┘ └──────────────────┘
│
┌───────▼───────────────────────────────────┐
│ Orchestration & Storage │
│ PostgreSQL | Redis | FAISS | Kubernetes │
└───────────────────────────────────────────┘
Core Technologies
AI Models
| Model | Purpose | License | VRAM |
|---|---|---|---|
| YuE | Full song generation | Apache 2.0 | 24-80GB |
| DiffRhythm | Fast rhythm synthesis | Apache 2.0 | 8GB |
| MusicGen | Controllable music gen | MIT | 8-24GB |
| JASCO | Chord-conditioned gen | MIT | 8GB |
Production Stack
- DAW: Ardour 8.8+ (GPL)
- Audio Server: Jack Audio
- Plugin Host: Carla
- MIDI Rendering: FluidSynth
- Source Separation: Demucs v4
- Transcription: Spotify Basic Pitch
- Database: PostgreSQL 15+
- Cache: Redis
- Vector Search: FAISS
- Orchestration: Kubernetes + Tilt
Documentation
Research Documents
Comprehensive research and planning documents located in /docs:
-
- Complete pipeline exploration (text → MIDI → audio)
- Technology stack evaluation (MusicGen, Text2MIDI, FluidSynth)
- Virtual instruments and synthesis options
- Implementation roadmap and workflows
-
- Training methodologies for hip-hop and dubstep/EDM
- DGX Spark optimization strategies
- Dataset curation and preprocessing
- Fine-tuning recipes and best practices
- Multi-stage training approaches
-
Cutting-Edge Music AI 2024-2025
- Latest open source models survey
- ARM/Linux compatibility analysis
- Integration architecture for Ardour
- Installation guides and benchmarks
- Production workflows and examples
-
DGX Spark Production Architecture
- Memory allocation table (110GB optimized)
- Service dependency graph
- API communication patterns
- Performance expectations and benchmarks
- Deployment strategy and monitoring
Project Structure
dgx-music/
├── docs/ # Research and documentation
├── services/ # Microservices
│ ├── orchestrator/ # Main orchestration agent
│ ├── generation/ # AI generation workers
│ ├── rendering/ # Audio rendering services
│ └── integration/ # Ardour/DAW integration
├── k8s/ # Kubernetes manifests
├── scripts/ # Nushell automation scripts
├── configs/ # Configuration files
├── Justfile # Task automation
├── Tiltfile # Development environment
└── README.md # This file
Development Workflow
Prerequisites
- NVIDIA DGX Spark with CUDA 12.1+
- Kubernetes cluster (or local k3s)
- Tilt CLI
- Just command runner
- Nushell
Common Tasks
# Initialize project
just init
# Start development environment
tilt up
# Run tests
just test
# Generate music (example)
just generate "trap beat with 808 bass 140 BPM"
# Train custom model
just train-model hip-hop dataset/
# Deploy to production
just deploy productionRoadmap
Phase 1: Foundation (Weeks 1-2)
- Research compilation
- Infrastructure setup
- Basic MIDI pipeline
- Ardour integration prototype
Phase 2: AI Integration (Weeks 3-4)
- Model deployment (MusicGen, DiffRhythm)
- Generation API
- Real-time transcription
- Stem separation
Phase 3: Production (Weeks 5-6)
- Kubernetes deployment
- Performance optimization
- Monitoring and logging
- User workflows
Phase 4: Advanced Features (Weeks 7-8)
- Genre-specific fine-tuning
- Multi-track generation
- Style transfer
- Production presets
Contributing
This project uses an orchestrator/subagent pattern for development. See CONTRIBUTING.md for details on:
- Development workflow
- Code standards
- Testing requirements
- Issue management
Performance
Expected performance on DGX Spark:
| Operation | Latency | Throughput |
|---|---|---|
| 16s music generation | 12-18s | 3.5 req/min |
| MIDI → Audio rendering | 0.5-1.2s | 20+ req/min |
| Audio-to-MIDI transcription | <1s | Real-time |
| Full song (4m45s) | ~10s | DiffRhythm |
License
- Code: Apache 2.0
- Models: See individual model licenses in documentation
- Research: CC-BY-4.0
Acknowledgments
Built on research from:
- Meta AI Research (AudioCraft, Demucs)
- Stability AI (Stable Audio)
- Spotify Research (Basic Pitch)
- ASLP Lab (DiffRhythm)
- M-A-P/HKUST (YuE)
- Ardour Community
Citation
If you use this work in research, please cite:
@software{dgx_music_2025,
title = {DGX Music: AI-Powered Music Production Platform},
author = {Raibid Labs},
year = {2025},
url = {https://github.com/raibid-labs/dgx-music}
}Contact
- Issues: GitHub Issues
- Discussions: GitHub Discussions
Status: Research Complete, Implementation in Progress Last Updated: November 6, 2025 Version: 0.1.0-alpha