Compressible lattice Boltzmann simulations on high‐performance and low‐cost GeForce GPU

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


Author(s):  
E Calore ◽  
A Gabbana ◽  
SF Schifano ◽  
R Tripiccione

High-performance computing systems are more and more often based on accelerators. Computing applications targeting those systems often follow a host-driven approach, in which hosts offload almost all compute-intensive sections of the code onto accelerators; this approach only marginally exploits the computational resources available on the host CPUs, limiting overall performances. The obvious step forward is to run compute-intensive kernels in a concurrent and balanced way on both hosts and accelerators. In this paper, we consider exactly this problem for a class of applications based on lattice Boltzmann methods, widely used in computational fluid dynamics. Our goal is to develop just one program, portable and able to run efficiently on several different combinations of hosts and accelerators. To reach this goal, we define common data layouts enabling the code to exploit the different parallel and vector options of the various accelerators efficiently, and matching the possibly different requirements of the compute-bound and memory-bound kernels of the application. We also define models and metrics that predict the best partitioning of workloads among host and accelerator, and the optimally achievable overall performance level. We test the performance of our codes and their scaling properties using, as testbeds, HPC clusters incorporating different accelerators: Intel Xeon Phi many-core processors, NVIDIA GPUs, and AMD GPUs.


2020 ◽  
Vol 16 (3) ◽  
pp. 246-253
Author(s):  
Marcin Gackowski ◽  
Marcin Koba ◽  
Stefan Kruszewski

Background: Spectrophotometry and thin layer chromatography have been commonly applied in pharmaceutical analysis for many years due to low cost, simplicity and short time of execution. Moreover, the latest modifications including automation of those methods have made them very effective and easy to perform, therefore, the new UV- and derivative spectrophotometry as well as high performance thin layer chromatography UV-densitometric (HPTLC) methods for the routine estimation of amrinone and milrinone in pharmaceutical formulation have been developed and compared in this work since European Pharmacopoeia 9.0 has yet incorporated in an analytical monograph a method for quantification of those compounds. Methods: For the first method the best conditions for quantification were achieved by measuring the lengths between two extrema (peak-to-peak amplitudes) 252 and 277 nm in UV spectra of standard solutions of amrinone and a signal at 288 nm of the first derivative spectra of standard solutions of milrinone. The linearity between D252-277 signal and concentration of amironone and 1D288 signal of milrinone in the same range of 5.0-25.0 μg ml/ml in DMSO:methanol (1:3 v/v) solutions presents the square correlation coefficient (r2) of 0,9997 and 0.9991, respectively. The second method was founded on HPTLC on silica plates, 1,4-dioxane:hexane (100:1.5) as a mobile phase and densitometric scanning at 252 nm for amrinone and at 271 nm for milrinone. Results: The assays were linear over the concentration range of 0,25-5.0 μg per spot (r2=0,9959) and 0,25-10.0 μg per spot (r2=0,9970) for amrinone and milrinone, respectively. The mean recoveries percentage were 99.81 and 100,34 for amrinone as well as 99,58 and 99.46 for milrinone, obtained with spectrophotometry and HPTLC, respectively. Conclusion: The comparison between two elaborated methods leads to the conclusion that UV and derivative spectrophotometry is more precise and gives better recovery, and that is why it should be applied for routine estimation of amrinone and milrinone in bulk drug, pharmaceutical forms and for therapeutic monitoring of the drug.


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