In theory, efficient and high-quality rendering of unstructured data should greatly benefit from
modern GPUs, but in practice, GPUs are often limited by the large amount of memory that …

Volume data these days is usually massive in terms of its topology, multiple fields, or
temporal component. With the gap between compute and memory performance widening …

MGARD (MultiGrid Adaptive Reduction of Data) is an algorithm for compressing and
refactoring scientific data, based on the theory of multigrid methods. The core algorithm is …

The rapidly growing size and complexity of 3D geological models has increased the need
for level-of-detail techniques and compact encodings to facilitate interactive visualization …

Solvers for partial differential equations (PDEs) are one of the cornerstones of computational
science. For large problems, they involve huge amounts of data that need to be stored and …

Des méthodes de simulation employant des maillages sont mises en oeuvre dans de
nombreux champs scientifiques pour caractériser des phénomènes physiques sous-jacents …

In this chapter we introduce a method for rendering large reservoir grids that do not fit into
GPU memory. We use a multiresolution method where the reservoir is represented in …

Research has entered a data-intensive era. The growing quantity of scientific information
challenges several application domains. That happens notably for the simulation science …

Le volume des données scientifiques produites par simulation numérique est en
augmentation croissante. Cette volumétrie incite depuis peu la communauté à employer des …

Manipulation of large data volumes is becoming a concern in the field of simulation. In
reservoir simulation, grids are complex structures composed of heterogeneous objects, with …