We design and develop a new high performance implementation of a fast direct LU-based
solver using low-rank approximations on massively parallel systems. The LU factorization is …

Neural architecture search (NAS), which automates the design of neural network (NN)
architectures for scientific datasets, requires significant computational resources and time …

Task‐based systems have become popular due to their ability to utilize the computational
power of complex heterogeneous systems. A typical programming model used is the …

In this paper, we describe and evaluate an extension of the CHAMELEON library to operate
with hierarchical matrices (H-Matrices) and hierarchical arithmetic (H-Arithmetic), producing …

In this paper, we describe and evaluate an extension of the Chameleon library to operate
with hierarchical matrices (H-Matrices) and hierarchical arithmetic (H-Arithmetic), producing …

In the last decades, the computing power of high-performance platforms has grown
exponentially at the expense of increased complexity. Programming such platforms to take …

Structured dense matrices result from boundary integral problems in electrostatics and
geostatistics, and also Schur complements in sparse preconditioners such as multi-frontal …

The LU factorization of hierarchical matrices (H-matrices) is a challenging problem for
efficient parallelization, due to complex dependency patterns. Previous research suggested …

This paper adresses static resource allocation problems for irregular distributed parallel
applications. More precisely, we focus on two classical tiled linear algebra kernels: the …

To leverage the extreme parallelism of emerging architectures, so that scientific applications
can fulfill their high fidelity and multi-physics potential while sustaining high efficiency …