traceR is a profiling framework for the R language to analyze the resource usage of an R application to locate bottlenecks. traceR consists of two modified R interpreters, one for runtime measurements called timeR and r-instrumented for analyzing runtime and memory behavior. The results are gathered in an SQLite database for convenient analysis. The current version of traceR was inspired by the original traceR from the Reactor group at Purdue University. This version has improved usability and analysis capability compared to the original. We added profiling for vector data structures, dynamic memory and CPU utilization profiles and profiling for parallel R programs.
References in zbMATH (referenced in 1 article )
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- Kotthaus, Helena; Korb, Ingo; Lang, Michel; Bischl, Bernd; Rahnenführer, Jörg; Marwedel, Peter: Runtime and memory consumption analyses for machine learning R programs (2015)