Scaling up the sparse matrix-vector multiplication kernel on modern Graphics Processing Units (GPU) has been at the heart of numerous studies in both academia and industry. In thi...
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...
Several methods have been proposed in the literature for the distribution of data on distributed memory machines, either oriented to dense or sparse structures. Many of the real a...
We consider the sparse grid combination technique for regression, which we regard as a problem of function reconstruction in some given function space. We use a regularised least ...
In this paper we describe the architecture and initial performance analysis results of the SERVOGrid Complexity Computational Environments (CCE). The CCE architecture is based on ...
Galip Aydin, Mehmet S. Aktas, Geoffrey Fox, Harsha...