We consider the problem of supporting compacting garbage collection in the presence of modern compiler optimizations. Since our collector may move any heap object, it must accurately locate, follow, and update all pointers and values derived from pointers. To assist the collector, we extend the compiler to emit tables describing live pointers, and values derived from pointers, at each program location where collection may occur. Significant results include identification of a number of problems posed by optimizations, solutions to those problems, a working compiler, and experimental data concerning table sizes, table compression, and time overhead of decoding tables during collection. While gc support can affect the code produced, our sample programs show no significant changes, the table sizes are a modest fraction of the size of the optimized code, and stack tracing is a small fraction of total gc time. Since the compiler enhancements are also modest, we conclude that the approach is...

To use modern hardware effectively, compilers need extensive control-flow information. Unfortunately, the frequent method invocations in object-oriented languages obscure control flow. In this paper, we describe and evaluate a range of analysis techniques to convert method invocations into direct calls for statically-typed object-oriented languages and thus improve control-flow information in object-oriented languages. We present simple algorithms for type hierarchy analysis, aggregate analysis, and interprocedural and intraprocedural type propagation. These algorithms are also fast, O(jproceduresj P procedures p n p v p ) worst case time (linear in practice) for our slowest analysis, where n p is the size of procedure p and v p is the number of variables in procedure p, and are thus practical for use in a compiler. When they fail, we introduce cause analysis to reveal the source of imprecision and suggest where more powerful algorithms may be warranted. We show that our simple an...

Abstract not found

Pointer traversals pose significant overhead to the execution of object-oriented programs, since every access to an object?s state requires a pointer dereference. Eliminating redundant pointer traversals reduces both instructions executed as well as redundant memory accesses to relieve pressure on the memory subsystem. We describe an approach to elimination of redundant access expressions that combines partial redundancy elimination (PRE) with type-based alias analysis (TBAA). To explore the potential of this approach we have implemented an optimization framework for Java class files incorporating TBAA-based PRE over pointer access expressions. The framework is implemented as a class-file-to-class-file transformer; optimized classes can then be run in any standard Java execution environment. Our experiments demonstrate improvements in the execution of optimized code for several Java benchmarks running in diverse execution environments: the standard interpreted JDK virtual machine, a virtual machine using ?just-in-time? compilation, and native binaries compiled off-line (?way-ahead-of-time?). Overall, however, our experience is of mixed success with the optimizations, mainly because of the isolation between our optimizer and the underlying execution environments which prevents more effective cooperation between them.We isolate the impact of access path PRE using TBAA, and demonstrate that Java?s requirement of precise exceptions can noticeably impact code-motion optimizations like PRE.

....................................... x 1 INTRODUCTION . . . . . . ........................... 1 1.1 Optimization framework ........................... 1 1.2 Measurements................................. 2 1.3 Overview ................................... 2 2 BACKGROUND .................................. 3 2.1 Controlflowgraphs.............................. 3 2.1.1 Dominators . . . ........................... 3 2.1.2 Loops . . . . . . ........................... 4 2.2 Staticsingleassignmentform......................... 6 2.2.1 Construction . . ........................... 7 2.2.2 Destruction . . . ........................... 11 2.3 Partial redundancy elimination . . . . .................... 12 2.3.1 SSAPRE . . . . ........................... 12 2.4 Other optimizations . . . ........................... 14 2.5 Typebasedaliasanalysis........................... 15 2.5.1 Terminology and notation . . .................... 16 v Page 2.5.2 TBAA . . . . . . ........................