HeAT: The Helmholtz Analytics ToolKit

Kurzfassung

HeAT is a distributed tensor framework for high performance data analytics. The goal of HeAT is to fill the gap between machine learning libraries that have a strong focus on exploiting GPUs for performance, and traditional, distributed high-performance computing (HPC). The basic idea is to provide a generic, distributed tensor library with machine learning methods based on it.