Demonstrator: Bridging between Data Science and Performance Analysis
Speaker: Elias Werner
Date: September 8th 2022, 1 p.m. – 2 p.m.
Location: ScaDS.AI Living Lab (APB-1020), Andreas-Pfitzmann-Bau (APB), Nöthnitzer Str. 46, 01187 Dresden, Germany
In the last years, an increasing amount of available data has led to new application approaches and an application field that is now called data science. Such applications often require low runtimes while having to deal with restricted compute resources. Up to now, we perceive that the data science community lacks tool support for runtime and resource usage investigations. Thus, we present an approach that combines data science and performance analysis from the High Performance Computing domain. Our concept integrates the measurement framework Score-P in Jupyter, a popular editor for the development of data science applications. We designed and implemented a custom Jupyter kernel that collects runtime data and applied it to a natural language processing application. The measurement overhead was 12.55 seconds. The benefits are, that the collected data can then be visualised using established performance analysis tools.
In the ScaDS.AI Living Lab Hands-On Demonstrator Series, we showcase the latest accomplishments, discoveries, improvements and educational tools of the ScaDS.AI team in the field of AI, Big Data and Data Science. The introductory talk, Q&A and hands-on session will provide you with a chance to familiarize yourself with the demonstrator.