Online Performance Analysis with the Vampir Tool Set

Abstract

Today, performance analysis of parallel applications is mandatory to fully exploit the capabilities of modern HPC systems. Many performance analysis tools are available to support users in this challenging task. All tools usually employ one of two analysis methodologies. The majority of analysis tools, such as HPCToolkit or Vampir, follow a post-mortem analysis approach. In this approach, a measurement infrastructure records performance data during the application execution and flushes its data to the file system. The tools perform subsequent analysis steps after the application execution by using the stored performance data. Post-mortem analysis comes with the disadvantage that possibly large data volumes need to be handled by the I/O subsystem of the machine. Tools following an online analysis approach mitigate this disadvantage by avoiding the I/O subsystem. The measurement infrastructure of these tools uses the network to directly transfer the recorded performance data to the analysis components of the tool. This approach, however, comes with the limitation that the complete analysis occurs at application runtime. In this work we present a prototype implementation of Vampir capable of performing online analysis. We discuss advantages and disadvantages of both approaches and draw conclusions for designing an online performance analysis tool.