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Green Configuration: Can AI Help In Reducing Energy Consumption Of Configurable Software Systems?.pdf

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Preview of Green Configuration: Can AI Help in Reducing Energy Consumption of Configurable Software Systems?
🔗 Source: se.cs.uni-saarland.de
📊 Size: 523 KB
📄 Pages: 8 pages
⬇️ Downloads: 63

Summary

Reducing energy consumption of IT systems is crucial for saving costs and reducing CO2 emissions. Configurable software systems offer a largely untapped potential for energy optimization through their configuration options. Artificial intelligence (AI) and machine learning (ML) can help users find energy-optimized configurations and developers identify configuration-related code regions for energy debugging. However, ML alone is insufficient for answering developers' questions, especially when causal relationships need to be revealed. A combination of software engineering (SE) methods and ML is necessary to build white-box energy models, providing accurate energy estimates and pointing developers to configuration-dependent code regions of causal interest.

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Description

Reducing energy consumption of IT systems is crucial for saving costs and reducing CO2 emissions.

Technical Information

  • File Format: PDF
  • File Size: 523 KB
  • Pages: 8
  • Language: EN
  • Total Downloads: 63
  • Last Updated: 1 month ago

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This PDF document about Green Configuration: Can AI Help in Reducing Energy Consumption of Configurable Software Systems? provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Green Configuration: Can AI Help in Reducing Energy Consumption of Configurable Software Systems?.

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