An annotation-aware Java virtual machine implementation

Abstract

SUMMARYThe Java bytecode language lacks expressiveness for traditional compiler optimizations, making this portable, secure software distribution format inefficient as a program representation for high performance. This inefficiency results from the underlying stack model, as well as the fact that many bytecode operations intrinsically include sub-operations (e.g. iaload includes the address computation, array bounds checks and the actual load of the array element). The stack model, with no operand registers and limiting access to the top of the stack, prevents the re-use of values and bytecode re-ordering. In addition, the language has no mechanism to indicate which sub-operations in the Java bytecode stream are redundant or subsumed by previous ones. As a consequence, the Java bytecode language inhibits the expression of important compiler optimizations, including register allocation and instruction scheduling.The Java bytecode stream generated by a Java bytecode compiler is a significantly under-optimized program representation. The most common solution to overcome this inefficiency is the use of a just-in-time (JIT) compiler to not only generate native code, but perform optimization as well. However, the latter is a time-consuming operation in an already time-constrained translation process. In this paper we present an alternative to an optimizing JIT compiler that makes use of code annotations generated by a Java bytecode compiler. These annotations carry information concerning compiler optimizations. During the translation process, an annotation-aware Java Virtual Machine (JVM) system then uses this information to produce high-performance native code without performing much of the necessary analyses or transformations. We describe the implementation of a prototype of an annotation-aware JVM consisting of an annotation-aware JIT compilation system. We conclude the paper showing performance results comparing our system with other JVMs running on SPARC architecture.

Instrumenting annotated programs

“…However, if attributes expected by a tool are absent from the class file, or are no longer valid because of instrumentation, the tool may function incorrectly. Annotations on bytecode were applied in research, for example, to pass information from a static compiler to JIT [18,30,2,13], or to store program analysis results [28].…”

“…Figure 1 illustrates the use of both @WebMethod and @array null check on the same method. 2 Suppose that the code in Figure 1 is instrumented to create a method-level profile of the application. We have already seen that modifying the method code renders @array null check unusable.…”

“…Had the instrumentation known the semantics of the offset field, it could have fixed the offset in the annotation, but recall that the semantics of annotation fields is generally unknown 2. To avoid confusion, we use the Java style (@Annotation) rather than C# style ([Annotation]) throughout this paper.…”