Array operations are important for large number of scientific and engineering applications.
Two-dimensional array operations are prominent in these applications because of their …

Degree of data sparsity increases with the increase of number of dimensions in high
performance scientific computing. Storing and applying operations on this highly sparse …

The computation on Graphics Processing Unit (GPU) has come out as a new cost-effective
parallel computing paradigm for high performance computing that makes possible to …

Array-based storage system employs a renewed interest in the featured applications for their
easy maintenance in the context of large volume data. However, the conventional schemes …

Matrix factorization, a widely used technique in various data analysis domains, is extended
to address the challenges of incremental data updates while maintaining computational …

We present a new implementation scheme of multidimensional array for handling large
scale high dimensional datasets that grows incrementally. The scheme implements a …

Conventional computing techniques extensively diverge over large scale computing. In
order to store and operate structured data, most data scientists suggest higher dimensional …

Several meetings of the Extremely Large Databases Community for large scale scientific
applications advocate the use of multidimensional arrays as the appropriate model for …

Several meetings of the Extremely Large Databases Community for large scale scientific
applications, advocate the use of multidimensional arrays as the appropriate model for …

Clustered VLIW embedded processors have become widespread due to benefits of simple
hardware and low power. However, while some applications exhibit large amounts of …