Sparse matrix-vector multiplication forms the heart of iterative linear solvers used widely in scientific computations (e.g., finite element methods). In such solvers, the matrix-v...
We describe the parallelization of an efficient algorithm for balanced truncation that allows to reduce models with state-space dimension up to O(105 ). The major computational tas...
Abstract—A novel approach for reconstruction of sparse highresolution data from lower-resolution dense spatio-temporal data is introduced. The basic idea is to compute the dense ...
Analysis of massive graphs has emerged as an important area for massively parallel computation. In this paper, it is shown how the Fresh Breeze trees-of-chunks memory model may be...
Run-time support for the CYCLIC(k) redistribution on the SPMD computation model is presently very relevant for the scientific community. This work is focused to the characterizati...