Semirings, automata, languages
Semirings, automata, languages
Characterising tractable constraints
Artificial Intelligence
Theoretical Computer Science
The first-order theory of subtyping constraints
POPL '02 Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Distributed Algorithms
Complexity and Approximation: Combinatorial Optimization Problems and Their Approximability Properties
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
Forward and Backward Simulations for Timing-Based Systems
Proceedings of the Real-Time: Theory in Practice, REX Workshop
LICS '96 Proceedings of the 11th Annual IEEE Symposium on Logic in Computer Science
Weak bisimulation for (max/+) automata and related models
Journal of Automata, Languages and Combinatorics - Special issue: Selected papers of the workshop weighted automata: Theory and applications (Dresden University of Technology (Germany), March 4-8, 2002)
Experimental analysis of the fastest optimum cycle ratio and mean algorithms
ACM Transactions on Design Automation of Electronic Systems (TODAES)
From sequential programs to multi-tier applications by program transformation
Proceedings of the 32nd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Links: web programming without tiers
FMCO'06 Proceedings of the 5th international conference on Formal methods for components and objects
Type-safe distributed programming with ML5
TGC'07 Proceedings of the 3rd conference on Trustworthy global computing
Explaining constraint programming
Processes, Terms and Cycles
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Placement inference assigns locations to operations in a distributed program under the constraints that some operations can only execute on particular locations and that values may not be transferred arbitrarily between locations. An optimal choice of locations additionally minimizes the run time of the program, given that operations take different time on different locations and that a cost is associated to transferring a value from one location to another.We define a language with a time- and location-aware semantics, formalize placement inference in terms of constraints, and show that solving these constraints is an NP-complete problem. We then show that optimal placements are computable via a reformulation of the semantics in terms of matrices and an application of the max-plus spectral theory. A prototype implementation validates our results.