scholarly journals High performance computing in chemistry and massively parallel computers: A simple transition?

1993 ◽  
Vol 48 (S27) ◽  
pp. 769-779 ◽  
Author(s):  
Rick A. Kendall
2014 ◽  
Author(s):  
Mehdi Gilaki ◽  
Ilya Avdeev

In this study, we have investigated feasibility of using commercial explicit finite element code LS-DYNA on massively parallel super-computing cluster for accurate modeling of structural impact on battery cells. Physical and numerical lateral impact tests have been conducted on cylindrical cells using a flat rigid drop cart in a custom-built drop test apparatus. The main component of cylindrical cell, jellyroll, is a layered spiral structure which consists of thin layers of electrodes and separator. Two numerical approaches were considered: (1) homogenized model of the cell and (2) heterogeneous (full) 3-D cell model. In the first approach, the jellyroll was considered as a homogeneous material with an effective stress-strain curve obtained through experiments. In the second model, individual layers of anode, cathode and separator were accounted for in the model, leading to extremely complex and computationally expensive finite element model. To overcome limitations of desktop computers, high-performance computing (HPC) techniques on a HPC cluster were needed in order to get the results of transient simulations in a reasonable solution time. We have compared two HPC methods used for this model is shared memory parallel processing (SMP) and massively parallel processing (MPP). Both the homogeneous and the heterogeneous models were considered for parallel simulations utilizing different number of computational nodes and cores and the performance of these models was compared. This work brings us one step closer to accurate modeling of structural impact on the entire battery pack that consists of thousands of cells.


Author(s):  
Gabriele Jost ◽  
Alice E. Koniges

The upcoming years bring new challenges in high-performance computing (HPC) technology. Fundamental changes in the building blocks of HPC hardware are forcing corresponding changes in programming models to effectively use these new architectures. The changes in store for HPC will rival the vector to massively parallel transition that scientific and engineering codes and methodologies endured several years ago. We describe some of the upcoming trends in hardware designs, and suggest ways in which software and programming models will advance accordingly.


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