Jerry P. Draayer

Learn More
Hierarchical storage formats (HSFs) can significantly reduce the space complexity of sparse matrices. They vary in storage schemes that they use for blocks and for block matrices. However, the current HSFs prescribe a fixed storage scheme for all blocks, which is not always space-optimal. We show that, generally, different storage schemes are space-optimal(More)
A new representation of a sparse matrix is introduced that is very efficient for matrix multiplication when the nonzero elements are partially or fully adjacent to one another as in band or triangular matrices. Space complexity is better than that of the existing algorithms when the number of the groups of adjacent non-zero elements is less than two-thirds(More)
Clear evidence for symplectic symmetry in low-lying states of 12C and 16O is reported. Eigenstates of 12C and 16O, determined within the framework of the no-core shell model using the J-matrix inverse scattering potential with A<or=16 (JISP16) nucleon-nucleon (NN) realistic interaction, typically project at the 85%-90% level onto a few of the most deformed(More)
Sparse matrix-vector multiplication (SpMV) is one of the most important numerical core methods in scientific and engineering computing. On today’s petascale and future exascale systems, the three principal problems related to SpMV are the minimization of communication between processors in distributed-memory environments, the maximization of the efficiency(More)
C++ does not support run-time resolution of template type arguments. To circumvent this restriction, we can instantiate a template for all possible combinations of type arguments at compile time and then select the proper instance at run time by evaluation of some provided conditions. However, for templates with multiple type parameters such a solution may(More)