Donald Bren School of Information and Computer Sciences

The Java Bytecodes language lacks expressiveness for traditional compiler optimizations making this portable, secure software distribution format inefficient as a program representation to produce high performance native code from. The fact that some bytecode operations intrinsically enclose implicit sub-operations (e.g., iaload, includes the address computation, array bound checks and the actual load of the array element) allied to the fact that Java Bytecodes language implements a stack model account for this inefficiency. The language has no mechanism to indicate which sub-operations in the bytecode stream are redundant or subsumed by previous ones. The stack model having no operand registers and restricting access to only the top of the stack is also a limitation as it prevents the reuse of values and bytecode reordering. As a consequence the language inhibits the expression of simple compiler transformations, such as common sub-expression elimination md loop invariant removal, and more elaborate ones as register allocation and instruction scheduling.

Regardless of how optimized the bytecode stream is generated by the Java front-end, it misses ability to represent some code-improving transformations. When translating the bytecodes into native code, JIT technology has the options of directly translating the bytecodes into a poor native code or enhancing the quality of this translated code by applying code optimizations. This second alternative leads to a more time consuming translation process in the already time-constrained JIT technology. In this paper we present an alternative to an optimizing JIT compiler that makes use of code cumotations generated by the Java front-end. These annotations carry information concerning compiler optimizations. In the translation process, an annotation-aware JIT (AJIT) system can use the annotation information to produce high performance native code without performing the code analysis and sometimes the transformations necessary for cin optimizing JIT compiler. We describe the implementation of the first prototype of our annotation-generating compiler and our annotation-aware JIT system and show performance results comparing our system with other Java Virtual Machines (JVMs) running on SPARC machines.