There has recently been a resurgence in interest in techniques for effective programming of multi-core computers. Most programmers find general-purpose concurrent programming to be extremely difficult. This difficulty severely limits the number of applications that currently benefit from multi-core computers. There already exist many concurrent solutions for the class of regular applications, which include various algorithms for linear algebra. For the class of irregular applications, which operate on dynamic and pointer- and graph-based structures, efficient concurrent solutions have so far remained elusive. Dataflow analysis applications, which are often found in compilers and program analysis tools, have received particularly little attention with regard to execution on multi-core machines. Operating on the theory that the Actor model, which structures computations as systems of asynchronously-communicating entities, is a more appropriate method for representing irregular algorithms than the shared-memory model, this work presents a concurrent Actor-based formulation of the IFDS, or Interprocedural Finite Distributive Subset, dataflow analysis algorithm. The implementation of this algorithm is done using the Scala language and its Actors library. This algorithm achieves significant speedup on multi-core machines without using any optimistic execution. This work contributes to Actor research by showing how the Actor model can be practically applied to a dataflow analysis problem. This work contributes to static analysis research by showing how a dataflow analysis algorithm can effectively make use of multi-core machines, allowing the possibility of faster and more precise analyses.

There has recently been a resurgence in interest in techniques for effective programming of multi-core computers. Most programmers find general-purpose concurrent programming to be extremely difficult. This difficulty severely limits the number of applications that currently benefit from multi-core computers. There already exist many concurrent solutions for the class of regular applications, which include various algorithms for linear algebra. For the class of irregular applications, which operate on dynamic and pointer- and graph-based structures, efficient concurrent solutions have so far remained elusive. Dataflow analysis applications, which are often found in compilers and program analysis tools, have received particularly little attention with regard to execution on multi-core machines. Operating on the theory that the Actor model, which structures computations as systems of asynchronously-communicating entities, is a more appropriate method for representing irregular algorithms than the shared-memory model, this work presents a concurrent Actor-based formulation of the IFDS, or Interprocedural Finite Distributive Subset, dataflow analysis algorithm. The implementation of this algorithm is done using the Scala language and its Actors library. This algorithm achieves significant speedup on multi-core machines without using any optimistic execution. This work contributes to Actor research by showing how the Actor model can be practically applied to a dataflow analysis problem. This work contributes to static analysis research by showing how a dataflow analysis algorithm can effectively make use of multi-core machines, allowing the possibility of faster and more precise analyses.