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is increasingly recognized that asthma represents
a syndrome, and there is clinical and pathobiological heterogeneity. Many genes
are reported to be associated with asthma, and may be involved in the disease
heterogeneity. Diverse cells, such as T helper 1 (Th1)-cells, Th2-cells,
Th17-cells, airway epithelial cells, and innate and adaptive immunity
associated cells, contribute to the pathobiology of asthma independently of
each other or they can also coexist and interact. Although, generally, Th2
immunity is important in most asthma endotypes, non- Th2-driven inflammation
tends to be difficult to manage. Recently, increased attention has been focused
on severe asthma and glucocorticoid (GC)-resistant (GC-R) asthma, in which
diverse inflammatory processes may be involved. Treatment approaches should
take into account pathological differences.
General purpose computing on GPU for scientific computing has been rapidly growing in recent years. We investigate the applicability of GPU to discrete element method (DEM) often used in particle motion simulation. NVIDIA provides a sample code for this type of simulation, which obtained superior performance than CPU in computational time. A computational model of the contact force in NVIDIA’s sample code is, however, too simple to use in practice. This paper modifies the NVIDIA’s simple model by replacing it with the practical model. The computing speed of the practical model on GPU is compared with the simple one on GPU and with the practical one on CPU in numerical experiments. The result shows that the practical model on GPU obtains the computing speed 6 times faster than the practical one on CPU while 7 times slower than that of the simple one on GPU. The effects of the GPU architectures on the computing speed are analyzed.