Profiling A Parallel Domain Specific Language Using Off-The-Shelf Tools

Mr Majed Al Saeed, University of Glasgow

Profiling tools are essential for understanding and tuning the performance of both parallel programs and parallel language implementations.  Assessing the performance of a program in a language with high-level parallel coordination is often complicated by the layers of abstraction present in the language and its implementation. We investigate whether it is possible to profile parallel Domain Specific Languages (DSLs) using existing host language profiling tools.  The key challenge is that the host language tools report the performance of the DSL runtime system (RTS) executing the application rather than the performance of the DSL application. The key questions are whether a correct, effective and efficient profiler can be constructed using host language profiling tools; is it possible to effectively profile the DSL implementation, and what capabilities are required of the host language profiling tools? We develop a profiler for the parallel DSL, Haskell Distributed Parallel Haskell (HdpH) using the host language profiling tools. We show that it is possible to construct a profiler (HdpHProf) to support performance analysis of both the DSL applications and the DSL implementation.  The implementation uses several new GHC features, including the Ghc-Events Library and ThreadScope, and for the first time two performance analysis tools for DSL HdpH internals, i.e. Spark Pool Contention Analysis, and Registry Contention Analysis.