Name
Abstract | ||
|---|---|---|
Historically, compilers have operated by applying a fixed set of optimizations in a predetermined order. We call such an ordered list of optimizations a compilation sequence. This paper describes a prototype system that uses biased random search to discover a program-specific compilation sequence that minimizes an explicit, external objective function. The result is a compiler framework that adapts its behavior to the application being compiled, to the pool of available transformations, to the objective function, and to the target machine.This paper describes experiments that attempt to characterize the space that the adaptive compiler must search. The preliminary results suggest that optimal solutions are rare and that local minima are frequent. If this holds true, biased random searches, such as a genetic algorithm, should find good solutions more quickly than simpler strategies, such as hill climbing. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1023/A:1015729001611 | The Journal of Supercomputing |
Keywords | Field | DocType |
configurable compilers,order of optimization,biased random search,optimizing compilers | Random search,Hill climbing,Computer science,Parallel computing,Maxima and minima,Theoretical computer science,Compiler,Genetic algorithm,Distributed computing | Journal |
Volume | Issue | ISSN |
23 | 1 | 1573-0484 |
Citations | PageRank | References |
92 | 5.11 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Keith D. Cooper | 1 | 1726 | 229.37 |
| Devika Subramanian | 2 | 687 | 120.10 |
| Linda Torczon | 3 | 1096 | 146.31 |