Abstract
The lack of direct support for multidimensional arrays in Java™ has been recognized as a major deficiency in the language's applicability to numerical computing. It has been shown that, when augmented with multidimensional arrays, Java can achieve very high-performance for numerical computing through the use of compiler techniques and efficient implementations of aggregate array operations. Three approaches have been discussed in the literature for extending Java with support for multidimensional arrays: class libraries that implement these structures; extending the Java language with new syntactic constructs for multidimensional arrays that are directly translated to bytecode; and relying on the Java Virtual Machine to recognize those arrays of arrays that are being used to simulate multidimensional arrays. This paper presents a balanced presentation of the pros and cons of each technique in the areas of functionality, language and virtual machine impact, implementation effort, and effect on performance. We show that the best choice depends on the relative importance attached to the different metrics, and thereby provide a common ground for a rational discussion and comparison of the techniques.