In our recent work, we have been working on providing parallel sparse supports for array intrinsics of Fortran 90. Our supporting library uses a two-level design. In the low-level routines, it requires the input sparse matrices to be speciied with compression/distribution schemes for array functions. In the high-level representations, sparse array functions are overloaded with Fortran 90 array ...

Sparse Matrix is a matrix consisting of very few non-zero entries. Large sparse matrices are often used in engineering and scientific operations. Especially sparse-matrix vector multiplication is an important operation for solving linear system and partial differential equations. However, there is a possibility that even though the matrix is partitioned and stored appropriately, the performance...

Simulation optimization today is an important branch in the field of heuristic optimization problems. Several simulators include built-in optimization and several companies have emerged that offer optimization strategies for different simulators. Often the optimization strategy is a secret and only sparse information is known about its inner workings. In this paper we want to demonstrate how th...

We consider a pair of collectively oscillating networks dynamical elements and optimize their internetwork coupling for efficient mutual synchronization based on the phase reduction theory developed by Nakao et al. [Chaos 28, 045103 (2018)]. The equations describing weakly coupled are reduced to equations, linear stability synchronized state between is represented as function matrix. seek optim...

We propose a method to estimate dense motion vector fields from multi-exposure images. Our approach relies on finding a sparse set of correspondences between features in a single-exposure image and each exposure in a multi-exposure image using a global optimization technique. We iteratively establish such matches, compute a set of locally restricted transformations for the matches, and construc...