# RustyTorch++ Demo Platform

A comprehensive suite of GPU-accelerated demos powered by RustyTorch++, packaged as a single-binary Tauri desktop application. Features 18 interactive demos across medical imaging, scientific computing, AI/ML, finance, and computer vision.

## Overview

All demos use the unified **rtx-tensor** backend for GPU acceleration, supporting:
- NVIDIA CUDA (Windows/Linux)
- Apple Metal (M1/M2/M3/M4/M5)
- CPU fallback (all platforms)

## Demo Categories

### Medical / Science (6 demos)

| Demo | Description | Physics/Algorithm |
|------|-------------|-------------------|
| **Virtual Catheter** | Real-time hemodynamics PINN | Inverse Navier-Stokes |
| **MRE Elastography** | Tissue stiffness estimation | Inverse Helmholtz |
| **Thermal Ablation** | 3D thermal therapy simulation | Pennes Bioheat Equation |
| **SlideScope Pathology** | Stain separation for digital pathology | Non-negative Matrix Factorization |
| **RustyNeuro MEG/EEG** | Neuroimaging analysis platform | Signal processing, source localization |
| **Medical Digital Twin** | Patient-specific ablation planning | Interactive physics simulation |

### AI / ML (6 demos)

| Demo | Description | Model/Method |
|------|-------------|--------------|
| **Neural Operator PDE** | Real-time PDE solving | Fourier Neural Operator (FNO) |
| **Physics-Informed Diffusion** | Generative PDE solving | PIDDM (diffusion + physics loss) |
| **FNO Benchmark** | Compare solvers | FNO vs FEM vs FDM |
| **PINN Benchmark** | Multi-PDE benchmark | Heat, Burgers, Poisson equations |
| **Inference Profiler** | Model performance analysis | Latency, throughput, memory |
| **Model Zoo** | Pre-trained model gallery | Classification, detection, NLP |

### Finance (3 demos)

| Demo | Description | Method |
|------|-------------|--------|
| **Portfolio Optimizer** | Mean-variance optimization | Markowitz efficient frontier |
| **Risk Analyzer** | VaR and stress testing | Monte Carlo simulation |
| **Time Series Forecast** | Multi-model forecasting | ARIMA, Prophet, Transformer |

### Vision (3 demos)

| Demo | Description | Model |
|------|-------------|-------|
| **Image Classifier** | Real-time classification | ViT, ConvNeXt (ImageNet) |
| **Object Detector** | Bounding box detection | YOLOv8 (COCO 80 classes) |
| **Segmentation** | Pixel-wise segmentation | DeepLabV3, SegFormer, UNet |

## Architecture

```
demos/
├── shared/                     # Hemodynamics IPC types
├── mre-shared/                 # MRE elastography types
├── bioheat-shared/             # Bioheat transfer types
├── slidescope-shared/          # SlideScope types
├── neuro-shared/               # RustyNeuro types
├── neural-operator-shared/     # FNO demo types
├── piddm-shared/               # Physics-informed diffusion types
├── digital-twin-shared/        # Digital twin types
├── fno-benchmark-shared/       # FNO benchmark types
├── pinn-benchmark-shared/      # PINN benchmark types
├── inference-profiler-shared/  # Inference profiler types
├── model-zoo-shared/           # Model zoo types
├── portfolio-shared/           # Portfolio optimizer types
├── risk-shared/                # Risk analyzer types
├── timeseries-shared/          # Time series types
├── image-classifier-shared/    # Image classifier types
├── object-detector-shared/     # Object detector types
├── segmentation-shared/        # Segmentation types
│
├── rtx-hemodynamics/           # Virtual Catheter backend
├── rtx-mre/                    # MRE elastography backend
├── rtx-bioheat/                # Bioheat simulation backend
├── rtx-slidescope/             # SlideScope NMF backend
├── rtx-neuro/                  # RustyNeuro backend
├── rtx-neural-operator-demo/   # FNO demo backend
├── rtx-piddm-demo/             # PIDDM backend
├── rtx-digital-twin-demo/      # Digital twin backend
├── rtx-fno-benchmark/          # FNO benchmark backend
├── rtx-pinn-benchmark/         # PINN benchmark backend
├── rtx-inference-profiler/     # Inference profiler backend
├── rtx-model-zoo/              # Model zoo backend
├── rtx-portfolio/              # Portfolio optimizer backend
├── rtx-risk-analyzer/          # Risk analyzer backend
├── rtx-timeseries/             # Time series backend
├── rtx-image-classifier/       # Image classifier backend
├── rtx-object-detector/        # Object detector backend
├── rtx-segmentation-demo/      # Segmentation backend
│
├── server/                     # Service layer (all demos)
└── ui/                         # Tauri + React frontend
```

## Quick Start

```bash
# Install dependencies
cd demos/ui
pnpm install

# Development mode
pnpm tauri dev

# Production build
pnpm tauri build
```

## Demo Details

### Medical / Science

#### 1. Virtual Catheter (Hemodynamics)

Solves the **inverse Navier-Stokes problem** - inferring pressure fields from velocity data for non-invasive virtual catheterization.

**Features:**
- Real-time PINN inference with GPU acceleration
- Interactive geometry editing (stenosis, aneurysm, stent)
- Pulsatile flow animation with cardiac waveforms
- Multi-field visualization (velocity, pressure, WSS)

**Physics:**
```
Momentum: ρ(∂u/∂t + u·∇u) = -∇p + μ∇²u
Continuity: ∇·u = 0
```

#### 2. MRE Elastography

Estimates tissue stiffness from MRI wave propagation using the **Helmholtz equation**.

**Features:**
- 2D/3D stiffness map reconstruction
- Wave field visualization
- Configurable frequency and wavelength
- Real-time GPU-accelerated solver

**Physics:**
```
∇²u + k²u = 0  (Helmholtz)
G = ρω²/k²     (Shear modulus estimation)
```

#### 3. Thermal Ablation (Bioheat)

Simulates thermal therapy using the **Pennes bioheat equation**.

**Features:**
- 3D temperature field simulation
- Heat source placement and configuration
- Thermal dose (CEM43) calculation
- Treatment planning visualization

**Physics:**
```
ρc(∂T/∂t) = k∇²T + ρ_b·c_b·ω_b(T_a - T) + Q
```

#### 4. SlideScope Pathology

GPU-accelerated stain separation using **Non-negative Matrix Factorization**.

**Features:**
- H&E and IHC stain unmixing
- Deep zoom tile viewing
- Real-time processing with progress
- Unified rtx-tensor backend

**Algorithm:**
```
V ≈ W × H  (NMF decomposition)
```

#### 5. RustyNeuro MEG/EEG

Comprehensive neuroimaging analysis platform.

**Features:**
- Signal visualization and filtering
- Epoching and averaging
- Source localization
- Connectivity analysis
- Inspired by Brainstorm

#### 6. Medical Digital Twin

Patient-specific organ simulation for treatment planning.

**Features:**
- Organ geometry selection
- Probe placement configuration
- Interactive bioheat simulation
- What-if analysis

### AI / ML

#### 7. Neural Operator PDE

Real-time PDE solving with Fourier Neural Operators.

**Features:**
- Draw boundary conditions interactively
- Instant solutions for Darcy flow, heat equation
- 1000x faster than traditional methods
- Train custom models

#### 8. Physics-Informed Diffusion (PIDDM)

Generative PDE solving with physics-consistent diffusion.

**Features:**
- Train diffusion models with physics loss
- Sample PDE solutions
- Supports Poisson, Heat, Darcy, Burgers
- Physics consistency visualization

#### 9. FNO Benchmark

Compare Neural Operators vs classical solvers.

**Features:**
- Side-by-side: FNO vs FEM vs FDM
- Resolution sweep (32x32 to 256x256)
- Metrics: time, accuracy, memory
- CSV export

#### 10. PINN Benchmark

Interactive Physics-Informed Neural Network benchmark.

**Features:**
- Heat, Burgers, Poisson equations
- Training convergence visualization
- Architecture comparison
- Loss curve charts

#### 11. Inference Profiler

Model performance analysis tool.

**Features:**
- Latency metrics (p50, p95, p99)
- Throughput measurement
- Memory profiling
- GPU utilization
- Batch size sweeps

#### 12. Model Zoo

Pre-trained model gallery for common ML tasks.

**Features:**
- Image classification (ResNet, ViT, ConvNeXt)
- Object detection (YOLO)
- Segmentation (DeepLab, SegFormer)
- Text generation, NLP, audio
- One-click inference

### Finance

#### 13. Portfolio Optimizer

Mean-variance portfolio optimization.

**Features:**
- Efficient frontier visualization
- Asset correlation matrix
- Risk/return trade-off analysis
- GPU-accelerated covariance estimation

#### 14. Risk Analyzer

Value-at-Risk and stress testing.

**Features:**
- Historical and parametric VaR
- Monte Carlo simulation
- Stress scenarios
- Risk decomposition

#### 15. Time Series Forecast

Multi-model time series forecasting.

**Features:**
- ARIMA/SARIMA models
- Prophet integration
- Transformer architectures
- Confidence intervals
- Sample datasets

### Vision

#### 16. Image Classifier

Real-time image classification.

**Features:**
- ViT and ConvNeXt models
- 1000 ImageNet classes
- GPU acceleration
- Confidence visualization

#### 17. Object Detector

YOLO-style object detection.

**Features:**
- YOLOv8 variants (Nano to XLarge)
- 80 COCO classes
- Adjustable confidence threshold
- NMS configuration
- Bounding box visualization

#### 18. Segmentation

Pixel-wise semantic segmentation.

**Features:**
- DeepLabV3, SegFormer, UNet, FCN
- PASCAL VOC (21 classes)
- ADE20K (150 classes)
- Cityscapes (19 classes)
- Mask overlay visualization

## GPU Backend

All demos use **rtx-tensor** for GPU operations:

```toml
[features]
default = ["cpu"]
cpu = ["rtx-tensor/cpu"]
cuda = ["rtx-tensor/cuda"]
metal = ["rtx-tensor/metal"]
```

### Supported Operations
- Matrix multiplication (matmul)
- Element-wise operations (add, sub, mul, div)
- Activation functions (relu, sigmoid, tanh, gelu, silu)
- Trigonometric functions (sin, cos) for Fourier features
- Reduction operations (sum, mean, max, min)
- Transpose, reshape, convolution

## Testing

```bash
# Run all backend tests
cargo test --workspace -p "*-shared" -p "rtx-*"

# Run specific demo tests
cargo test -p rtx-hemodynamics
cargo test -p inference-profiler-shared
cargo test -p segmentation-shared

# Frontend tests
cd demos/ui && pnpm test
```

### Test Coverage

| Category | Crates | Tests |
|----------|--------|-------|
| Medical/Science | 12 | 600+ |
| AI/ML | 12 | 500+ |
| Finance | 6 | 200+ |
| Vision | 6 | 250+ |
| **Total** | **36** | **1,550+** |

## Performance Targets

| Metric | Target |
|--------|--------|
| Inference latency | <50ms for 10k points |
| UI responsiveness | 30+ FPS |
| GPU memory | <2GB per simulation |
| Build time | <5 min full rebuild |

## License

Part of RustyTorch++. See repository root for license information.