Data Parallel Computing

Unlike process concurrency, parallelism of data is a language issue. In this important area of parallel computing, using an appropriate programming paradigm with clear semantics and a deliberate structure may significantly alter the software design methodology. In this book, the authors address the language aspect of data-parallel computing by critically evaluating several well-known languages: APL, Fortran-90 and HPF. They also introduce new languages: EVAL and F-code.

The many design highlights, examples, and especially the treatment of all languages from a single point of view makes this book invaluable to software developers. It should also appeal to researchers, academics and students in the field of parallel computing. The book comes with some free software, in particular a full implementation of EVAL. Readers will find this in the authors' archive at ftp://www.ee.surrey.ac.uk/pub/DPar on the Internet.