HPC has undergone a significant transition toward heterogeneous architectures. This
transition has introduced several issues in code migration to support multiple frameworks for …

A wide range of scientific and machine learning applications depend on highly optimized
implementations of tensor computations. Exploiting the full capacity of a given processor …

We present a methodology for precision tuning of full applications. These techniques must
select a search space composed of either variables or instructions and provide a scalable …

The advent to exascale requires more scalable and efficient techniques to help developers
to locate, analyze and correct errors in parallel applications. PARallel COntrol flow Anomaly …

Many areas of science exhibit physical processes that are described by high dimensional
partial differential equations (PDEs), eg, the 4D (Dorf et al., 2013), 5D (Candy et al., 2009) and …

Supercomputers are rapidly evolving with now millions of processing units, posing the
questions of their programmability. Despite the emergence of more widespread and functional …

The complexity of High Performance Computing nodes memory system increases in order
to challenge application growing memory usage and increasing gap between computation …

Optimizing the implementation of tensor computations is essential to exploiting the full
capacity of a given processor architecture on a wide range of scientific and machine learning …

Le Calcul Haute Performance, regroupant l’ensemble des acteurs responsables de l’amélioration
des performances de calcul des applications scientifiques sur supercalculateurs, s’est …

Ocean simulation models often underperform on modern high-performance computing (HPC)
architectures, necessitating costly and time-consuming code rewrites. We introduce …