Pasqua D’Ambra

Research Director

Institute for Applied Computing of the National Research Council and CINI National Lab. on HPC-KTT



Node-level efficiency and scalability issues in iterative sparse linear solvers at scale

In this talk, I will present activities aimed at designing and developing algorithms and mathematical software that enable scientific and engineering applications to face the exascale challenge. Resolution needs of high-fidelity numerical simulations reach numbers of degrees of freedom which go beyond O(10^10) and are in an increasing trend. This generally imposes a rethinking of numerical algorithms and solvers to exploit high degrees of parallelism and complexity of the current (and near-future) high-end supercomputers. I will focus on iterative solvers for linear algebraic equations arising in physics-driven scientific simulation and present parallel efficiency and scalability results from engineering applications in the energy sector. The activities are developed at the HPC Lab of IAC-CNR in the context of some European projects and of the Italian National Center on HPC, Big Data and Quantum Computing.

Short bio

Pasqua D’Ambra earned her PhD in Applied Mathematics and Computer Science from the University of Naples Federico II, Italy, in 1995. Her research interests are in parallel numerical algorithms and mathematical software with applications to Computational and Data Science. Her activities are carried on in the context of national and international projects, also with PI roles.


  • Algebraic multilevel preconditioners and sparse iterative linear solvers at scale
  • Spectral clustering of complex networks
  • HPC simulation modeling in computational fluid dynamics