Summary of the SciTech 2020 Technical Panel on In Situ/In Transit Computational Environments for Visualization and Data Analytics

2021 ◽  
Author(s):  
Earl P. Duque ◽  
Steve M. Legensky ◽  
Brad J. Whitlock ◽  
David H. Rogers ◽  
Andrew C. Bauer ◽  
...  
Keyword(s):  
Data Analytics ◽  
In Transit

In Situ and In Transit Computing for Large Scale Geoscientific Simulation

2020 ◽  
Author(s):  
Sebastian Friedemann ◽  
Bruno Raffin ◽  
Basile Hector ◽  
Jean-Martial Cohard
Keyword(s):  
Data Assimilation ◽  
High Performance ◽  
Large Scale ◽  
Transfer Model ◽  
Simulation Data ◽  
Computing Platform ◽  
Continental Scale ◽  
Physically Based ◽  
In Transit

<p>In situ and in transit computing is an effective way to place postprocessing and preprocessing tasks for large scale simulations on the high performance computing platform. The resulting proximity between the execution of preprocessing, simulation and postprocessing permits to lower I/O by bypassing slow and energy inefficient persistent storages. This permits to scale workflows consisting of heterogeneous components such as simulation, data analysis and visualization, to modern massively parallel high performance platforms. Reordering the workflow components gives a manifold of new advanced data processing possibilities for research. Thus in situ and in transit computing are vital for advances in the domain of geoscientific simulation which relies on the increasing amount of sensor and simulation data available.</p><p>In this talk, different in situ and in transit workflows, especially those that are useful in the field of geoscientific simulation, are discussed. Furthermore our experiences augmenting ParFlow-CLM, a physically based, state-of-the-art, fully coupled water transfer model for the critical zone, with FlowVR, an in situ framework with a strict component paradigm, are presented.<br>This allows shadowed in situ file writing, in situ online steering and in situ visualization.</p><p>In situ frameworks further can be coupled to data assimilation tools.<br>In the on going EoCoE-II we propose to embed data assimilation codes into an in transit computing environment. This is expected to enable ensemble based data assimilation on continental scale hydrological simulations with multiple thousands of ensemble members.</p>

scholarly journals Melanoma in situ with in-transit metastases

JPRAS Open ◽  
2017 ◽  
Vol 11 ◽  
pp. 37-42
Author(s):  
Joachim Mikkelsen ◽  
Anne Lene Hagen Wagenblast ◽  
Nille Behrendt ◽  
Jørgen Lock-Andersen
Keyword(s):  
Melanoma In Situ ◽  
In Transit

scholarly journals In situ and in-transit analysis of cosmological simulations

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Brian Friesen ◽  
Ann Almgren ◽  
Zarija Lukić ◽  
Gunther Weber ◽  
Dmitriy Morozov ◽  
...  
Keyword(s):  
Cosmological Simulations ◽  
In Transit

In-Situ Fluid Rheological Behavior Characterization Using Data Analytics Techniques

2018 ◽  
Author(s):  
Reza Ettehadi ◽  
Roland May ◽  
Thomas Dahl ◽  
Dennis Clapper ◽  
Rosa Swartwout
Keyword(s):  
Rheological Behavior ◽  
Data Analytics ◽  
Using Data

scholarly journals In situ data analytics and indexing of protein trajectories

2017 ◽  
Vol 38 (16) ◽  
pp. 1419-1430 ◽  
Author(s):  
Travis Johnston ◽  
Boyu Zhang ◽  
Adam Liwo ◽  
Silvia Crivelli ◽  
Michela Taufer
Keyword(s):  
Data Analytics ◽  
In Situ Data
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