Profile

Dipl.-Ing. Jens Henrik Göbbert

Research Assistant


Publications


Bernd Hentschel, Jens Henrik Göbbert, Michael Klemm, Paul Springer, Andrea Schnorr, Torsten Wolfgang Kuhlen
Eurographics Symposium on Parallel Graphics and Visualization (2015)

The advection of integral lines is an important computational kernel in vector field visualization. We investigate how this kernel can profit from vector (SIMD) extensions in modern CPUs. As a baseline, we formulate a streamline tracing algorithm that facilitates auto-vectorization by an optimizing compiler. We analyze this algorithm and propose two different optimizations. Our results show that particle tracing does not per se benefit from SIMD computation. Based on a careful analysis of the auto-vectorized code, we propose an optimized data access routine and a re-packing scheme which increases average SIMD efficiency. We evaluate our approach on three different, turbulent flow fields. Our optimized approaches increase integration performance up to 5:6 over our baseline measurement. We conclude with a discussion of current limitations and aspects for future work.

» Show BibTeX
@INPROCEEDINGS{Hentschel2015, author = {Bernd Hentschel and Jens Henrik G{\"o}bbert and Michael Klemm and Paul Springer and Andrea Schnorr and Torsten W. Kuhlen}, title = {{P}acket-{O}riented {S}treamline {T}racing on {M}odern {SIMD} {A}rchitectures}, booktitle = {Proceedings of the Eurographics Symposium on Parallel Graphics and Visualization}, year = {2015}, pages = {43--52}, abstract = {The advection of integral lines is an important computational kernel in vector field visualization. We investigate how this kernel can profit from vector (SIMD) extensions in modern CPUs. As a baseline, we formulate a streamline tracing algorithm that facilitates auto-vectorization by an optimizing compiler. We analyze this algorithm and propose two different optimizations. Our results show that particle tracing does not per se benefit from SIMD computation. Based on a careful analysis of the auto-vectorized code, we propose an optimized data access routine and a re-packing scheme which increases average SIMD efficiency. We evaluate our approach on three different, turbulent flow fields. Our optimized approaches increase integration performance up to 5.6x over our baseline measurement. We conclude with a discussion of current limitations and aspects for future work.} }





Andrea Schnorr, Jens Henrik Göbbert, Torsten Wolfgang Kuhlen, Bernd Hentschel
Large Data Analysis and Visualization (LDAV), 2015

We present a novel approach for tracking space-filling features, i.e. a set of features which covers the entire domain. In contrast to previous work, we determine the assignment between features from successive time steps by computing a globally optimal, maximum-weight, maximal matching on a weighted, bi-partite graph. We demonstrate the method's functionality by tracking dissipation elements (DEs), a space-filling structure definition from turbulent flow analysis. The ability to track DEs over time enables researchers from fluid mechanics to extend their analysis beyond the assessment of static flow fields to time-dependent settings.

» Show BibTeX
@INPROCEEDINGS{Schnorr2015, author = {Andrea Schnorr and Jens-Henrik Goebbert and Torsten W. Kuhlen and Bernd Hentschel}, title = {{T}racking {S}pace-{F}illing {S}tructures in {T}urbulent {F}lows}, booktitle = Proc # { the } # LDAV, year = {2015}, pages = {143--144}, abstract = {We present a novel approach for tracking space-filling features, i.e. a set of features which covers the entire domain. In contrast to previous work, we determine the assignment between features from successive time steps by computing a globally optimal, maximum-weight, maximal matching on a weighted, bi-partite graph. We demonstrate the method's functionality by tracking dissipation elements (DEs), a space-filling structure definition from turbulent flow analysis. The abilitytotrack DEs over time enables researchers from fluid mechanics to extend their analysis beyond the assessment of static flow fields to time-dependent settings.}, doi = {10.1109/LDAV.2015.7348089}, keywords = {Feature Tracking, Weighted, Bi-Partite Matching, Flow Visualization, Dissipation Elements} }




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