Fine-Grained Content-Addressed Computation Reuse for Document Processing Pipelines

This master thesis addresses the problem of improving efficiency in document processing pipelines by enabling fine-grained computation reuse based on content addressing. The work proposes methods to identify and reuse intermediate computation results at a granular level to reduce redundant processing. By leveraging content-based hashing and pipeline analysis, the approach aims to optimize resource usage and processing time in document workflows. The contributions include designing algorithms and system architectures that support such reuse, evaluating their effectiveness in practical document processing scenarios, and demonstrating significant performance improvements over conventional pipeline executions. This research provides valuable insights and tools for enhancing the scalability and responsiveness of automated document processing systems.