Spar: a set of extensions Java for scientific computation

ABSTRACT

In this paper we present a set of language extensions that improve the expressiveness and performance of Java for scientific computation. First of all, the language extensions allow the manipulation of multi-dimensional arrays to be expressed more naturally, and to be implemented more efficiently. Furthermore, data-parallel programming is supported, allowing efficient parallelization of a large class of operations on arrays. We also provide language extensions to construct specialized array representations, such as symmetric, block, and sparse matrices. These extensions are: tuples, parameterized types, array subscript overloading, and the inline modifier. These extensions are not only useful to construct special array representations, but are also useful in their own right. Finally, we add complex numbers as a primitive type to the language.

We evaluate our language extensions using performance results. We also compare relevant code fragments of our extended language with standard Java implementations and language extensions proposed by others.

INDEX TERMS

Primary Classification:
  D. Software
  D.3 PROGRAMMING LANGUAGES
      D.3.2 Language Classifications

          Nouns: Java

Additional Classification:
  D. Software
  D.1 PROGRAMMING TECHNIQUES
      D.1.3 Concurrent Programming
          Subjects: Parallel programming

  E. Data
  E.1 DATA STRUCTURES
      Subjects: Arrays

General Terms:
Experimentation, Languages, Performance