By Janine Bennett, Fabien Vivodtzev, Valerio Pascucci
This ebook comprises papers provided on the Workshop at the research of Large-scale, High-Dimensional, and Multi-Variate info utilizing Topology and facts, held in Le Barp, France, June 2013. It beneficial properties the paintings of a few of the main fashionable and famous leaders within the box who learn demanding situations in addition to aspect recommendations to the research of maximum scale data.
The ebook offers new tools that leverage the mutual strengths of either topological and statistical innovations to aid the administration, research, and visualization of complicated info. It covers either thought and alertness and offers readers with an outline of vital key suggestions and the newest study trends.
Coverage within the booklet comprises multi-variate and/or high-dimensional research innovations, feature-based statistical tools, combinatorial algorithms, scalable facts algorithms, scalar and vector box topology, and multi-scale representations. additionally, the publication information algorithms which are greatly acceptable and will be utilized by program scientists to glean perception from a variety of complicated info sets.
Read or Download Topological and Statistical Methods for Complex Data: Tackling Large-Scale, High-Dimensional, and Multivariate Data Spaces PDF
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Extra info for Topological and Statistical Methods for Complex Data: Tackling Large-Scale, High-Dimensional, and Multivariate Data Spaces
Ribés et al. the IBM BG/Q. We did not, in this study, perform any delicate memory tweaking in order to reduce the memory consumption. We are currently working on this point, experimenting with the new VTK in-situ data structures implemented recently by Kitware, the so-called “zero copy VTK”. This approach aims to facilitate the memory management in the adaptor without the use of complicated pointer manipulation; we expect to reduce memory overhead without much increasing code complexity. Another ongoing development consists on how we deal with the ghost levels generated by Code_Saturne.
Both built upon the well known parallel visualization library VTK, the application frameworks VisIt  and ParaView  both provide through the possibility to co-process simulation data via libsim  and Catalyst  respectively. Those in-situ solutions are tightly coupled and while they limit potential interactions with the running simulation, they also highly reduce the need of network data transfer. Thus, they contribute to circumventing the inefficiency of high performance computing I/O systems.
The effective tradeoff is decreased RCB execution time versus increased time later in Phase 4 by the PEs that got more than the average number of points. The algorithm presented in this chapter used a modified version of RCB (not a randomized version). It chooses five potential pivot points that are evenly spaced through the volume. It then identifies the pair of pivots that contain the ideal pivot and places another five evenly spaced pivots between them. The best choice of those five is the pivot.