Run-time issues in program partitioning on distributed memory systems

Our earlier work reported a Threshold Scheduling Method for compile-time mapping of functional parallism on distributed-memory systems. The work reported in this paper discusses run-time issues in efficiently supporting the functional parallism with minimal overheads, through a combination of compile-time and run-time ownership analysis. At compile time, the code generation phase determines whether a local copy of a live definition of a variable needed by a task is available on a given processor, through an ownership analysis. In case ownership cannot be resolved at compile time, an appropriate code is generated to perform analysis at run time. The code generation is carried out so that all the processors carry the same copy of the compiled program with the individual processor's code being isolated and the universally owned code being replicated on all processors to minimize run-time overheads. The run-time system maintains the static and dynamic ownerships at every processor to avoid communication overhead on ownership information. We demonstrate the approach by incorporating it in the compiler for targeting a parallel functional language, Sisal (streams and iterations in single assignment language), to Intel Touchstone i860 systems. Several benchmarks demonstrate the viability of the approach.