Theory of linear and integer programming
Theory of linear and integer programming
Integer and combinatorial optimization
Integer and combinatorial optimization
Precoloring extension. I: Interval graphs
Discrete Mathematics - Special volume (part 1) to mark the centennial of Julius Petersen's “Die theorie der regula¨ren graphs”
Improvements to graph coloring register allocation
ACM Transactions on Programming Languages and Systems (TOPLAS)
ACM Transactions on Programming Languages and Systems (TOPLAS)
Optimal and near-optimal global register allocations using 0–1 integer programming
Software—Practice & Experience
Optimal spilling for CISC machines with few registers
Proceedings of the ACM SIGPLAN 2001 conference on Programming language design and implementation
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A faster optimal register allocator
Proceedings of the 35th annual ACM/IEEE international symposium on Microarchitecture
Register allocation & spilling via graph coloring
SIGPLAN '82 Proceedings of the 1982 SIGPLAN symposium on Compiler construction
Optimistic register coalescing
ACM Transactions on Programming Languages and Systems (TOPLAS)
Register allocation for programs in SSA-Form
CC'06 Proceedings of the 15th international conference on Compiler Construction
An optimistic and conservative register assignment heuristic for chordal graphs
CASES '07 Proceedings of the 2007 international conference on Compilers, architecture, and synthesis for embedded systems
Optimal polynomial-time interprocedural register allocation for high-level synthesis and ASIP design
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Register allocation by puzzle solving
Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation
Copy coalescing by graph recoloring
Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation
Advanced conservative and optimistic register coalescing
CASES '08 Proceedings of the 2008 international conference on Compilers, architectures and synthesis for embedded systems
Live-range unsplitting for faster optimal coalescing
Proceedings of the 2009 ACM SIGPLAN/SIGBED conference on Languages, compilers, and tools for embedded systems
Register allocation deconstructed
Proceedings of th 12th International Workshop on Software and Compilers for Embedded Systems
Progressive spill code placement
CASES '09 Proceedings of the 2009 international conference on Compilers, architecture, and synthesis for embedded systems
On minimizing register usage of linearly scheduled algorithms with uniform dependencies
Computer Languages, Systems and Structures
SSA-based register allocation with PBQP
CC'11/ETAPS'11 Proceedings of the 20th international conference on Compiler construction: part of the joint European conferences on theory and practice of software
CC'10/ETAPS'10 Proceedings of the 19th joint European conference on Theory and Practice of Software, international conference on Compiler Construction
Copy elimination on data dependence graphs
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Elimination of parallel copies using code motion on data dependence graphs
Computer Languages, Systems and Structures
Hardware acceleration for programs in SSA form
Proceedings of the 2013 International Conference on Compilers, Architectures and Synthesis for Embedded Systems
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Recent work has shown that the subtasks of register allocation (spilling, register assignment, and coalescing) can be completely separated. This work presents an algorithm for the coalescing subproblem that relies on this separation. The algorithm uses 0/1 Linear Programming (ILP), a general-purpose optimization technique, to derive optimal solutions. We provide the first optimal solutions for a benchmark called "Optimal Coalescing Challenge", i.e., our ILP model outperforms previous approaches. Additionally,we use these optimal solutions to assess the quality ofwell-known heuristics.Asecond benchmark on SPECCPU2000 programs emphasizes the practicality of our algorithm.