The algorithm of Multiple Relatively Robust Representations (MRRR or MR
eigenvalues and eigenvectors of a symmetric tridiagonal matrix in
) arithmetic operations. Large problems can be effectively tackled with existing distributed-memory parallel implementations of MRRR; small and medium size problems can instead make use of LAPACK’s routine
is optimized for single-core CPUs, and does not take advantage of today’s multi-core and future many-core architectures. In this paper we discuss some of the issues and trade-offs arising in the design of MR
–SMP, an algorithm for multi-core CPUs and SMP systems. Experiments on application matrices indicate that MR
–SMP is both faster and obtains better speedups than all the tridiagonal eigensolvers included in LAPACK and Intel’s Math Kernel Library (MKL).