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- README.md: Fleet overview and quick access commands - FLEET.md: Complete device specifications and inventory - NETWORK.md: IP addresses, Tailscale mesh, network diagram - SSH_CONFIG.md: SSH configuration reference - HAILO.md: Hailo-8 AI accelerator documentation Fleet: 8 devices, 52 TOPS AI compute, 167 Docker containers 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
90 lines
1.9 KiB
Markdown
90 lines
1.9 KiB
Markdown
# Hailo-8 AI Accelerator Setup
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## Overview
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Two Pironman Pi 5 units equipped with Hailo-8 M.2 AI accelerators.
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| Device | Serial Number | Firmware | TOPS |
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|--------|---------------|----------|------|
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| octavia | HLLWM2B233704606 | 4.23.0 | 26 |
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| cecilia | HLLWM2B233704667 | 4.23.0 | 26 |
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**Total AI Compute: 52 TOPS**
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## Hailo-8 Specifications
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- **Architecture**: HAILO8
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- **Part Number**: HM218B1C2FAE
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- **Product Name**: HAILO-8 AI ACC M.2 M KEY MODULE EXT TEMP
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- **Performance**: 26 TOPS (Tera Operations Per Second)
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- **Interface**: M.2 M-Key (PCIe)
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## Quick Commands
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### Check Hailo Status
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```bash
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# Identify device
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ssh octavia "hailortcli fw-control identify"
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# Scan for devices
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ssh octavia "hailortcli scan"
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# Check device exists
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ssh octavia "ls -la /dev/hailo0"
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```
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### Run Benchmark
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```bash
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# On cecilia (has sample models)
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ssh cecilia "hailortcli benchmark /usr/share/hailo-models/resnet_v1_50_h8l.hef -t 5"
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```
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### Sample Output
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```
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Network resnet_v1_50/resnet_v1_50: 100% | FPS: 23.98
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```
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## Available Models
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Located at `/usr/share/hailo-models/` on cecilia:
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- `resnet_v1_50_h10.hef`
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- `resnet_v1_50_h8l.hef`
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- `scrfd_2.5g_h8l.hef`
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## Pironman 5 Fan Service
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Both units run the Pironman 5 fan control service:
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```bash
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# Check status
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ssh octavia "systemctl status pironman5"
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# View settings
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ssh octavia "pironman5 --help"
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# RGB LED control
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ssh octavia "pironman5 -rc '#FF1D6C' -rs solid"
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```
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## HailoRT Service
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The Hailo runtime service runs automatically:
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```bash
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ssh cecilia "systemctl status hailort"
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```
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## Use Cases
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1. **Real-time Object Detection** - YOLO models at 30+ FPS
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2. **Image Classification** - ResNet, MobileNet
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3. **Face Detection** - SCRFD models
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4. **Edge AI Inference** - Low latency local processing
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## Integration Notes
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- Both devices have Docker installed for containerized AI workloads
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- Cecilia runs Ollama for LLM inference
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- NVMe storage available for model caching
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- Tailscale mesh enables remote AI inference calls
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