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What and Who
Title:Bridging the Performance Gap in Digital Geometry Processing
Speaker:Rhaleb Zayer
coming from:Max-Planck-Institut für Informatik - D4
Speakers Bio:
Event Type:Joint Lecture Series
Visibility:D1, D2, D3, INET, D4, D5, SWS, RG1, MMCI
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Level:Public Audience
Date, Time and Location
Date:Wednesday, 5 June 2019
Duration:60 Minutes
Building:E1 5
As the computing landscape is being reshaped by the dramatic shift towards ubiquitous parallelism, and by the sheer scale of data, extracting performance from existing applications gives rise to formidable challenges. In digital geometry processing, the problem gets amplified by data irregularity (e.g. meshes) and the predominately serial nature of traditional algorithmic solutions.  As a results the gap between the high performance promise of modern hardware and the actual performance seems to grow wider.

In this talk, I will discuss the impact of data structures and problem abstraction on performance. In particular, I will outline how high performance can be gained through a lean data representation which allows channeling parallelism through linear algebra kernels regardless of the underlying granularity. I will illustrate the impact of problem abstraction on challenging and far reaching scenarios including Voronoi diagrams (VD)/centroidal Voronoi tessellations (CVT) on surface meshes, subdivision surfaces, as well as matrix assembly in finite element analysis.
Name(s):Jennifer Müller
EMail:--email address not disclosed on the web
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Created:Jennifer Müller/MPI-INF, 02/27/2019 02:26 PM Last modified:Uwe Brahm/MPII/DE, 02/28/2019 07:01 AM
  • Jennifer Müller, 02/27/2019 02:28 PM -- Created document.