Supplement to “Prediction models for network-linked data”. We provide the proof of
theoretical properties, computational complexity, additional simulation examples under …

The rapid emergence of multicore machines has led to the need to design new algorithms
that are efficient on these architectures. Here, we consider the solution of sparse symmetric …

The ongoing hardware evolution exhibits an escalation in the number, as well as in the
heterogeneity, of computing resources. The pressure to maintain reasonable levels of …

The ongoing hardware evolution exhibits an escalation in the number, as well as in the
heterogeneity, of computing resources. The pressure to maintain reasonable levels of …

Direct methods for solving sparse systems of linear equations have a high asymptotic
computational and memory requirements relative to iterative methods. However, systems …

The current trend in the high performance computing shows a dramatic increase in the
number of cores on the shared memory compute nodes. Algorithms, especially those related …

Simulation of large scale seismic wave propagation is an important tool in seismology for
efficient strong motion analysis and risk mitigation. Being particularly CPU-consuming, this …

In the context of this thesis, our focus is on numerical linear algebra, more precisely on
solution of large sparse systems of linear equations. We focus on designing efficient parallel …

The solution of large sparse linear systems is a critical operation for many numerical
simulations. To cope with the hierarchical design of modern supercomputers, hybrid solvers …

To face the advent of multicore processors and the ever increasing complexity of hardware
architectures, programming models based on DAG-of-tasks parallelism regained popularity …