Solving Large-Scale Eigenvalue Problems on Vector Parallel Processors.

We consider the development and implementation of eigensolvers on distributed memory parallel arrays of vector processors and show that the concomitant requirements for vectorisation and parallelisation lead both to novel algorithms and novel implementation techniques. Performance results are given for several large-scale applications and some performance comparisons made with LAPACK and ScaLAPACK. [ABSTRACT FROM AUTHOR]