This paper presents a simple and efficient data flow algorithm for escape analysis of objects in Java programs to determine (i) if an object can be allocated on the stack; (ii) if an object is accessed only by a single thread duriing its lifetime, so that synchronization operations on that object can be removed. We introduce a new program abstraction for escape analysis, the connection graph, that is used to establish reachability rela-tionships between objects and object references. We show that the connection graph can be summarized for each method such that the same summary information may be used effectively in different calling contexts. We present an interprocedural al-gorithm that uses the above property to efficiently compute the connection graph and identify the non-escaping objects for methods and threads. The experimental results, from a proto-type implementation of our framework in the IBM High Per-formance Compiler for Java, are very promising. The percent-age of objects that may be allocated on the stack exceeds 70% of all dynamically created objects in three out of the ten bench-marks (with a median of 19%), 11 % to 92 % of all lock oper-ations are eliminated in those ten programs (with a median of 5 l%), and the overall execution time reduction ranges from 2 % to 23 % (with a median of 7%) on a 333 MHz PowerPC workstation with 128 MB memory. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advant-age and that copies bear this notice and the full citation on the first page.

The goal of points-to analysis for Java is to determine the set of objects pointed to by a reference variable or a reference object field. This information has a wide variety of client applications in optimizing compilers and software engineering tools. In this paper we present a points-to analysis for Java based on Andersen's points-to analysis for C [5]. We implement the analysis by using a constraint-based approach which employs annotated inclusion constraints. Constraint annotations allow us to model precisely and efficiently the semantics of virtual calls and the flow of values through object fields. By solving systems of annotated inclusion constraints, we have been able to perform practical and precise points-to analysis for Java.

The goal of points-to analysis for Java is to determine the set of objects pointed to by a reference variable or a reference object field. We present object sensitivity, a new form of context sensitivity for flow-insensitive points-to analysis for Java. The key idea of our approach is to analyze a method separately for each of the object names that represent runtime objects on which this method may be invoked. To ensure flexibility and practicality, we propose a parameterization framework that allows analysis designers to control the tradeo#s between cost and precision in the object-sensitive analysis.

. Although there has been some experimentation with Java as a language for numerically intensive computing, there is a perception by many that the language is not suited for such work. In this paper we show how optimizing array bounds checks and null pointer checks creates loop nests on which aggressive optimizations can be used. Applying these optimizations by hand to a simple matrix-multiply test case leads to Java compliant programs whose performance is in excess of 500 Mflops on an RS/6000 SP 332MHz SMP node. We also report in this paper the effect that each optimization has on performance. Since all of these optimizations can be automated, we conclude that Java will soon be a serious contender for numerically intensive computing. 1 Introduction The scientific programming community has recently demonstrated a great deal of interest in the use of Java for technical computing. There are many compelling reasons for such use of Java: a large supply of programmers, it is obj...

Dynamic class loading during program execution in the Java Programming Language is an impediment for generating code that is as efficient as code generated using static whole-program analysis and optimization. Whole-program analysis and optimization is possible for languages, such as C++, that do not allow new classes and/or methods to be loaded during program execution. One solution for performing whole-program analysis and avoiding incorrect execution after a new class is loaded is to invalidate and recompile affected methods. Runtime invalidation and recompilation mechanisms can be expensive in both space and time, and, therefore, generally restrict optimization. To address these drawbacks, we propose a new framework, called the extant analysis framework, for interprocedural optimization of programs that support dynamic class (or method) loading. Given a set of classes comprising the closed world, we perform an offline static analysis which partitions references into two catego...

One glaring weakness of Java for numerical programming is its lack of support for complex numbers. Simply creating a Complex number class leads to poor performance relative to Fortran. We show in this paper, however, that the combination of such a Complex class and a compiler that understands its semantics does indeed lead to Fortran-like performance. This performance gain is achieved while leaving the Java language completely unchanged and maintaining full compatibility with existing Java Virtual Machines. We quantify the effectiveness of our approach through experiments with linear algebra, electromagnetics, and computational fluid-dynamics kernels. 1 Introduction The Java Grande Forum has identified several critical issues related to the role of Java (TM)1 in numerical computing [14]. One of the key requirements is that Java must support efficient operations on complex numbers. Complex arithmetic and access to elements of complex arrays must be as efficient as the manipulation o...

The goal of points-to analysis for Java is to determine the set of objects pointed to by a reference variable or a reference object field. In this paper we present a points-to analysis for Java based on Andersen's points-to analysis for C [5]. Andersen's analysis can be implemented efficiently by using systems of set-inclusion constraints and by employing several techniques for constraint representation and resolution. We extend these techniques to efficiently represent and solve systems of annotated inclusion constraints. The annotations play two roles in our analysis. Method annotations are used to model precisely and efficiently the semantics of virtual calls. Field annotations allow us to distinguish between different fields of an object. In addition, our analysis keeps track of all reachable methods and avoids analyzing irrelevant library code. We evaluate the performance of the analysis on a large set of realistic Java programs. Our experiments show that the analysis runs in practical...