Benchmarking Distributed Database Performance and Dependability under Partial System Failures

Many types of database management systems exist, but finding the one that is right for a specific use case is becoming increasingly more difficult. Benchmarks allow one to compare various systems, but in a world where distributed DBMSs are increasingly used for mission critical purposes, we find most existing benchmarks neglect fault tolerance...

Enriching Machine Learning Model Metadata: Collecting performance metadata through automatic evaluation

As the sharing of machine learning (ML) models has increased in popularity, more so-called model zoos are created. These repositories facilitate the sharing of models and their metadata, and other people to find and re-use an existing model. However, the metadata provided for models is insufficient, with little focus on practical aspects of a...