text: As applications grow in capability, they also grow in complexity. This complexity in turn gets pushed into modules and libraries. In addition, hardware configurations become increasingly elaborate, too. These two trends make understanding, debugging and analyzing the performance of applications more and more difficult.
  @cite_2: The Message-Passing Interface (MPI) is large and complex. Therefore, programming MPI is error prone. Several MPI runtime correctness tools address classes of usage errors, such as deadlocks or non-portable constructs. To our knowledge none of these tools scales to more than about 100 processes. However, some of the current HPC systems use more than 100,000 cores and future systems are expected to use far more. Since errors often depend on the task count used, we need correctness tools that scale to the full system size. We present a novel framework for scalable MPI correctness tools to address this need. Our fine-grained, module-based approach supports rapid prototyping and allows correctness tools built upon it to adapt to different architectures and use cases. The design uses P n MPI to instantiate a tool from a set of individual modules. We present an overview of our design, along with first performance results for a proof of concept implementation.
summary: One possible application for tools interfaces and library wrappers is to check for correct API usage. For example MUST @cite_2 uses MPI's profiling interface to ensure correct use and to detect possible deadlocks. The wrapping code is generated manually with a simple proprietary wrapper generator.