Parallelism for free: efficient and optimal bitvector analyses for parallel programs
ACM Transactions on Programming Languages and Systems (TOPLAS)
Advanced compiler design and implementation
Advanced compiler design and implementation
Efficient algorithms for pre* and post* on interprocedural parallel flow graphs
Proceedings of the 27th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
On the complexity of flow-sensitive dataflow analyses
Proceedings of the 27th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
A unified approach to global program optimization
POPL '73 Proceedings of the 1st annual ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Symbolic evaluation and the global value graph
POPL '77 Proceedings of the 4th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
Constraint-Based Inter-Procedural Analysis of Parallel Programs
ESOP '00 Proceedings of the 9th European Symposium on Programming Languages and Systems
Euro-Par '98 Proceedings of the 4th International Euro-Par Conference on Parallel Processing
Invariance of Approximate Semantics with Respect to Program Transformations
GI - 11. Jahrestagung in Verbindung mit Third Conference of the European Co-operation in Informatics (ECI)
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
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Despite of the well-known state-explosion problem, certain simple but important data-flow analysis problems known as gen/kill problems can be solved efficiently and completely for parallel programs with a shared state [7,6,2,3,13]. This paper shows that, in all probability, these surprising results cannot be generalized to significantly larger classes of data-flow analysis problems. More specifically, we study the complexity of detecting copy constants in parallel programs, a problem that may be seen as representing the next level of difficulty of data-flow problems beyond gen/kill problems. We show that already the intraprocedural problem for loop-free parallel programs is co-NP-complete and that the interprocedural problem is even PSPACE-hard.