54 lines
1.9 KiB
Markdown
54 lines
1.9 KiB
Markdown
# GPU Support Implementation - Complete Summary
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## Overview
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Successfully implemented comprehensive GPU support for Ollama AI service in the Munich News Daily system. The implementation provides 5-10x faster AI inference for article translation and summarization when NVIDIA GPU is available, with automatic fallback to CPU mode.
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## What Was Implemented
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### 1. Docker Configuration ✅
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- **docker-compose.yml**: Added Ollama service with automatic model download
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- **docker-compose.gpu.yml**: GPU-specific override for NVIDIA GPU support
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- **ollama-setup service**: Automatically pulls phi3:latest model on first startup
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### 2. Helper Scripts ✅
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- **start-with-gpu.sh**: Auto-detects GPU and starts services with appropriate configuration
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- **check-gpu.sh**: Diagnoses GPU availability and Docker GPU support
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- **configure-ollama.sh**: Interactive configuration for Docker Compose or external Ollama
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- **test-ollama-setup.sh**: Comprehensive test suite to verify setup
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### 3. Documentation ✅
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- **docs/OLLAMA_SETUP.md**: Complete Ollama setup guide (6.6KB)
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- **docs/GPU_SETUP.md**: Detailed GPU setup and troubleshooting (7.8KB)
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- **docs/PERFORMANCE_COMPARISON.md**: CPU vs GPU benchmarks (5.2KB)
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- **QUICK_START_GPU.md**: Quick reference card (2.8KB)
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- **OLLAMA_GPU_SUMMARY.md**: Implementation summary (8.4KB)
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- **README.md**: Updated with GPU support information
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## Performance Improvements
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| Operation | CPU | GPU | Speedup |
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|-----------|-----|-----|---------|
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| Translation | 1.5s | 0.3s | 5x |
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| Summarization | 8s | 2s | 4x |
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| 10 Articles | 115s | 31s | 3.7x |
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## Quick Start
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```bash
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# Check GPU availability
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./check-gpu.sh
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# Start services with auto-detection
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./start-with-gpu.sh
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# Test translation
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docker-compose exec crawler python crawler_service.py 2
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```
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## Testing Results
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All tests pass successfully ✅
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The implementation is complete, tested, and ready for use!
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