A study of a C function inliner
Software—Practice & Experience
Inline function expansion for compiling C programs
PLDI '89 Proceedings of the ACM SIGPLAN 1989 Conference on Programming language design and implementation
Knapsack problems: algorithms and computer implementations
Knapsack problems: algorithms and computer implementations
An experiment with inline substitution
Software—Practice & Experience
Profile-guided automatic inline expansion for C programs
Software—Practice & Experience
Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation
A comparative study of static and profile-based heuristics for inlining
DYNAMO '00 Proceedings of the ACM SIGPLAN workshop on Dynamic and adaptive compilation and optimization
An analysis of inline substitution for a structured programming language
Communications of the ACM
A methodology for procedure cloning
Computer Languages
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Function inlining is a powerful high level optimization which eliminates call cost and increases the chances of other optimizations taking effect due to the breaking down of the call boundaries. Goal-directed function cloning on the other hand strives to create specialized copies of functions to aid interprocedural optimizations. Both of these program transformations create additional code. In the traditional optimizers the problem of choosing which functions to inline is modelled as a 0-1 knapsack problem with a given budget. Function cloning is also treated likewise. However, the usual modelling considers these two as separate knapsack problems with their own respective budgets for code growth. This creates problems as independent budgets can give rise to excessive cloning or inlining and throttling opportunities for one or the other. To circumvent this problem we propose to formulate the inlining and cloning site selection problem as a uni ed multiple-choice knapsack problem. Multiple-choice knapsack is a well-studied problem in the domain of linear programming. In this paper we would look into a greedy algorithm to solve such knapsack problems and its application to the problem at hand.