Petascale lattice-Boltzmann studies of amphiphilic cubic liquid crystalline materials in a globally distributed high-performance computing and visualization environment

Author(s):  
Radhika S. Saksena ◽  
Marco D. Mazzeo ◽  
Stefan J. Zasada ◽  
Peter V. Coveney

We present very large-scale rheological studies of self-assembled cubic gyroid liquid crystalline phases in ternary mixtures of oil, water and amphiphilic species performed on petascale supercomputers using the lattice-Boltzmann method. These nanomaterials have found diverse applications in materials science and biotechnology, for example, in photovoltaic devices and protein crystallization. They are increasingly gaining importance as delivery vehicles for active agents in pharmaceuticals, personal care products and food technology. In many of these applications, the self-assembled structures are subject to flows of varying strengths and we endeavour to understand their rheological response with the objective of eventually predicting it under given flow conditions. Computationally, our lattice-Boltzmann simulations of ternary fluids are inherently memory- and data-intensive. Furthermore, our interest in dynamical processes necessitates remote visualization and analysis as well as the associated transfer and storage of terabytes of time-dependent data. These simulations are distributed on a high-performance grid infrastructure using the application hosting environment; we employ a novel parallel in situ visualization approach which is particularly suited for such computations on petascale resources. We present computational and I/O performance benchmarks of our application on three different petascale systems.

2007 ◽  
Author(s):  
Radhika Saksena ◽  
Peter V. Coveney ◽  
Robin Pinning ◽  
Stephen Booth

2015 ◽  
Vol 2015.28 (0) ◽  
pp. _241-1_-_241-2_
Author(s):  
Tomohiro Takaki ◽  
Shinji Sakane ◽  
Roberto Rojas ◽  
Munekazu Ohno ◽  
Yasushi ◽  
...  

2021 ◽  
Author(s):  
Murtadha Al-Habib ◽  
Yasser Al-Ghamdi

Abstract Extensive computing resources are required to leverage todays advanced geoscience workflows that are used to explore and characterize giant petroleum resources. In these cases, high-performance workstations are often unable to adequately handle the scale of computing required. The workflows typically utilize complex and massive data sets, which require advanced computing resources to store, process, manage, and visualize various forms of the data throughout the various lifecycles. This work describes a large-scale geoscience end-to-end interpretation platform customized to run on a cluster-based remote visualization environment. A team of computing infrastructure and geoscience workflow experts was established to collaborate on the deployment, which was broken down into separate phases. Initially, an evaluation and analysis phase was conducted to analyze computing requirements and assess potential solutions. A testing environment was then designed, implemented and benchmarked. The third phase used the test environment to determine the scale of infrastructure required for the production environment. Finally, the full-scale customized production environment was deployed for end users. During testing phase, aspects such as connectivity, stability, interactivity, functionality, and performance were investigated using the largest available geoscience datasets. Multiple computing configurations were benchmarked until optimal performance was achieved, under applicable corporate information security guidelines. It was observed that the customized production environment was able to execute workflows that were unable to run on local user workstations. For example, while conducting connectivity, stability and interactivity benchmarking, the test environment was operated for extended periods to ensure stability for workflows that require multiple days to run. To estimate the scale of the required production environment, varying categories of users’ portfolio were determined based on data type, scale and workflow. Continuous monitoring of system resources and utilization enabled continuous improvements to the final solution. The utilization of a fit-for-purpose, customized remote visualization solution may reduce or ultimately eliminate the need to deploy high-end workstations to all end users. Rather, a shared, scalable and reliable cluster-based solution can serve a much larger user community in a highly performant manner.


Nanoscale ◽  
2021 ◽  
Author(s):  
Qinghai Ma ◽  
Fang Cui ◽  
Mufei Liu ◽  
Jia jia Zhang ◽  
Tieyu Cui

The large-scale Ni-based nano-sized coordination polymers (Ni-nCPs) are facilely constructed by a self-assembled approach at room temperature and atmosphere pressure. In this strategy, we only use environmentally friendly solvents of...


2013 ◽  
Vol 5 (9) ◽  
pp. 3738-3747 ◽  
Author(s):  
Paramita Das ◽  
Susanne Schipmann ◽  
Jani-Markus Malho ◽  
Baolei Zhu ◽  
Uwe Klemradt ◽  
...  

Author(s):  
Jens Harting ◽  
Jonathan Chin ◽  
Maddalena Venturoli ◽  
Peter V Coveney

During the last 2.5 years, the RealityGrid project has allowed us to be one of the few scientific groups involved in the development of computational Grids. Since smoothly working production Grids are not yet available, we have been able to substantially influence the direction of software and Grid deployment within the project. In this paper, we review our results from large-scale three-dimensional lattice Boltzmann simulations performed over the last 2.5 years. We describe how the proactive use of computational steering, and advanced job migration and visualization techniques enabled us to do our scientific work more efficiently. The projects reported on in this paper are studies of complex fluid flows under shear or in porous media, as well as large-scale parameter searches, and studies of the self-organization of liquid cubic mesophases.


2019 ◽  
Vol 31 (20) ◽  
Author(s):  
Ruo‐Fan Qiu ◽  
Hai‐Ning Wang ◽  
Jian‐Feng Zhu ◽  
Rong‐Qian Chen ◽  
Cheng‐Xiang Zhu ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document