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HeAT - A New Versatile Distributed-Parallel Machine Learning Toolkit

Knechtges, Philipp (2019) HeAT - A New Versatile Distributed-Parallel Machine Learning Toolkit. PASC 2019, 2019-06-12 - 2019-06-14, ETH Zürich. (Unpublished)

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In this talk we will present the Helmholtz Analytics Toolkit (HeAT), a scientific big data analytics library for HPC systems. Big data analytics, and machine learning in particular, has gained a lot of traction recently with applications ranging from neuroscience to aeronautics. At the heart of many of these methods lies the idea to model even discrete decision processes with continuous functions, whose programmatic handling of course necessitates numerical linear algebra, a prime subject of HPC. However, many classical HPC algorithms are designed with sparsity in mind, a property most often inherited from the locality of a physical description. Since such a locality is missing a priori in most big data scenarios, it poses new challenges on the efficient algorithm design. We will discuss our current efforts to make such algorithms available to the broader public in the HeAT framework.

Item URL in elib:https://elib.dlr.de/132412/
Document Type:Conference or Workshop Item (Speech)
Title:HeAT - A New Versatile Distributed-Parallel Machine Learning Toolkit
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Knechtges, PhilippUNSPECIFIEDhttps://orcid.org/0000-0002-4849-0593UNSPECIFIED
Date:12 June 2019
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Keywords:Machine Learning, HeAT, HPC
Event Title:PASC 2019
Event Location:ETH Zürich
Event Type:international Conference
Event Start Date:12 June 2019
Event End Date:14 June 2019
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Vorhaben SISTEC (old)
Location: Köln-Porz
Institutes and Institutions:Institut of Simulation and Software Technology > High Performance Computing
Institut of Simulation and Software Technology
Deposited By: Knechtges, Philipp
Deposited On:10 Dec 2019 09:05
Last Modified:24 Apr 2024 20:35

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