Springer papers


Hrachya Astsatryan , V. Sahakyan , Yu. Shoukouryan , M. Daydé and A. Hurault


Scientific research is becoming increasingly dependent on the large-scale analysis of data using High Performance Computing (HPC) infrastructures. Scientific computing aims at constructing mathematical models and numerical solution techniques for solving problems arising in science and engineering. The solution of linear system of equations lies at the heart of most calculations in scientific computing. HPC infrastructures with many-core and graphics processing unit (GPU) challenges, Cloud and Grid technologies and e-infrastructures are currently offering interesting opportunities for solving large-scale linear system of equations. In this article, a second-generation of our Web portal for Scientific Computing is introduced based on a hybrid HPC infrastructure that provides predictable optimal execution and scales from a single resource to multiple resources. After analyzing the synergies and the complementarities of the different computing platforms, we argue for an architecture that combines the benefits of these technologies.


Linear Algebra P-Grade BLAS SGEMM CUBLAS GPU Grid Portal