Automatic loop transformations and parallelization for Java

Abstract

From a software engineering perspective, the Java programming language provides an attractive platform for writing numerically intensive applications. A major drawback hampering its widespread adoption in this domain has been its poor performance on numerical codes. This paper describes a prototype Java compiler which demonstrates that it is possible to achieve performance levels approaching those of current state-of-the-art C, C++ and Fortran compilers on numerical codes. We describe a new transformation called alias versioning that takes advantage of the simplicity of pointers in Java. This transformation, combined with other techniques that we have developed, enables the compiler to perform high order loop transformations (for better data locality) and parallelization completely automatically. We believe that our compiler is the first to have such capabilities of optimizing numerical Java codes. We achieve, with Java, between 80 and 100% of the performance of highly optimized Fortran code in a variety of benchmarks. Furthermore, the automatic parallelization achieves speedups of up to 3.8 on four processors. Combining this compiler technology with packages containing the features expected by programmers of numerical applications would enable Java to become a serious contender for implementing new numerical applications.