Demand-driven Partial Dead Code Elimination

抄録

Partial dead code elimination (PDE) is a powerful code optimization technique that extends dead code elimination based on code motion. PDE eliminates assignments that are dead on some execution paths and alive on others. Hence, it can not only eliminate partially dead assignments but also move loop-invariant assignments out of loops. These effects are achieved by interleaving dead code elimination and code sinking. Hence, it is important to capture second-order effects between them, which can be reflected by repetitions. However, this process is costly. This paper proposes a technique that applies PDE to each assignment on demand. Our technique checks the safety of each code motion so that no execution path becomes longer. Because checking occurs on a demand-driven basis, the checking range may be restricted. In addition, because it is possible to check whether an assignment should be inserted at the blocking point of the code motion by performing a demand-driven analysis, PDE analysis can be localized to a restricted region. Furthermore, using the demand-driven property, our technique can be applied to each statement in a reverse postorder for a reverse control flow graph, allowing it to capture many second-order effects. We have implemented our technique as a code optimization phase and compared it with previous studies in terms of optimization and execution costs of the target code. As a result, our technique is as efficient as a single application of PDE and as effective as multiple applications of PDE.