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A probabilistic pointer analysis for speculative optimizations (2006)
| Content Provider | CiteSeerX |
|---|---|
| Researcher | Silva, Jeffrey Da |
| Abstract | Pointer analysis is a critical compiler analysis used to disambiguate the indirect memory ref-erences that result from the use of pointers and pointer-based data structures. A conventional pointer analysis deduces for every pair of pointers, at any program point, whether a points-to relation between them (i) definitely exists, (ii) definitely does not exist, or (iii) maybe exists. Many compiler optimizations rely on accurate pointer analysis, and to ensure correctness can-not optimize in the maybe case. In contrast, recently-proposed speculative optimizations can aggressively exploit the maybe case, especially if the likelihood that two pointers alias could be quantified. This dissertation proposes a Probabilistic Pointer Analysis (PPA) algorithm that statically predicts the probability of each points-to relation at every program point. Building on simple control-flow edge profiling, the analysis is both one-level context and flow sensitive—yet can still scale to large programs. |
| File Format | |
| Publisher Date | 2006-01-01 |
| Access Restriction | Open |
| Subject Keyword | Probabilistic Pointer Analysis Speculative Optimization Points-to Relation Maybe Case Program Point Pointer Alias Accurate Pointer Analysis Correctness Can-not Optimize Recently-proposed Speculative Optimization Pointer-based Data Structure Conventional Pointer Analysis Deduces Large Program Indirect Memory Ref-erences Many Compiler Optimization Simple Control-flow Edge Profiling Pointer Analysis One-level Context Critical Compiler Analysis |
| Content Type | Text |
| Resource Type | Thesis |
