Abstract: This paper gives an overview of the implementation of NESL, a portable nested data-parallel language. This language and its implementation are the first to fully support nested data structures as well as nested data-parallel function calls. These features allow the concise description of parallel algorithms on irregular data structures, such as sparse matrices and graphs. In addition, they maintain the advantages of data-parallel languages: a simple programming model and portability. The current NESL implementation is based on an intermediate language called VCODE and a library of vector routines called CVL. It runs on the Connection Machines CM-2 and CM-5, the Cray C90, and serial workstations. We compare initial benchmark results of NESL with those of machine-specific code on these machines for three algorithms: least-squares line-fitting, median finding, and a sparse- matrix vector product. These results show that NESL's performance is competitive with that of machine-specific code for regular dense data, and is often superior for irregular data.
@techreport{nesl-impl,
author = "Guy~E. Blelloch and Siddhartha Chatterjee and
Jonathan~C. Hardwick and Jay Sipelstein and Marco Zagha",
title = "Implementation of a Portable Nested Data-Parallel Language",
institution = "School of Computer Science, Carnegie Mellon University",
number = "CMU-CS-93-112",
month = feb,
year = 1993 }