Schulze, Richard; Gorlatch, Sergei; Rasch, Ari
Forschungsartikel in Online-Sammlung (Konferenz) | Peer reviewedWe introduce pyATF—a new, language-independent, open-source auto-tuning tool that fully automatically determines optimized values of performance-critical program parameters. A major feature of pyATF is its support for constrained parameters, e.g., the value of one parameter has to divide the value of another parameter. A further major feature of pyATF is its user interface which is designed with a particular focus on expressivity and usability for real-world demands, and which is offered in the increasingly popular Python programming language. We experimentally confirm the practicality of pyATF using real-world studies from the areas of quantum chemistry, image processing, data mining, and deep learning: we show that pyATF auto-tunes the complex parallel implementations of our studies to higher performance than achieved by state-of-practice approaches, including hand-optimized vendor libraries.
| Gorlatch, Sergei | Professur für Praktische Informatik (Prof. Gorlatch) Institut für Informatik |
| Rasch, Ari | Professur für Praktische Informatik (Prof. Gorlatch) Institut für Informatik |
| Schulze, Richard Heinrich Hermann | Professur für Praktische Informatik (Prof. Gorlatch) Institut für Informatik |