ScalaJack: Customized scalable tracing with in-situ data analysis

Abstract

Root cause diagnosis of large-scale HPC applications often fails because tools, specifically trace-based ones, can no longer record all metrics they measure. We address this problems by combining customized tracing and providing support for in-situ data analysis via ScalaJack, a framework with customizable instrumentation and pluggable extension capabilities for problem directed instrumentation and in-situ data analysis. We further eliminate cross cutting concerns by code refactoring for aspect orientation and evaluate these capabilities in case studies within and beyond the scope of tracing. © 2014 Springer International Publishing Switzerland.