Ronny Tschüter, Johannes Ziegenbalg, Bert Wesarg, Matthias Weber, Christian Herold, Sebastian Döbel, and Ronny Brendel. 2017. An LLVM Instrumentation Plug-in for Score-P. In Proceedings of the Fourth Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC'17). ACM, New York, NY, USA, Article 2, 8 pages. DOI: https://doi.org/10.1145/3148173.3148187
Reducing application runtime, scaling parallel applications to higher numbers of processes/threads, and porting applications to new hardware architectures are tasks necessary in the software development process. Therefore, developers have to investigate and understand application runtime behavior. Tools such as monitoring infrastructures that capture performance relevant data during application execution assist in this task. The measured data forms the basis for identifying bottlenecks and optimizing the code.
Monitoring infrastructures need mechanisms to record application activities in order to conduct measurements. Automatic instrumentation of the source code is the preferred method in most application scenarios. We introduce a plug-in for the LLVM infrastructure that enables automatic source code instrumentation at compile-time. In contrast to available instrumentation mechanisms in LLVM/Clang, our plug-in can selectively include/exclude individual application functions. This enables developers to fine-tune the measurement to the required level of detail while avoiding large runtime overheads due to excessive instrumentation.Read Publication