Articles | Volume 12, issue 2
https://doi.org/10.5194/gmd-12-749-2019
https://doi.org/10.5194/gmd-12-749-2019
Development and technical paper
 | 
20 Feb 2019
Development and technical paper |  | 20 Feb 2019

MP CBM-Z V1.0: design for a new Carbon Bond Mechanism Z (CBM-Z) gas-phase chemical mechanism architecture for next-generation processors

Hui Wang, Junmin Lin, Qizhong Wu, Huansheng Chen, Xiao Tang, Zifa Wang, Xueshun Chen, Huaqiong Cheng, and Lanning Wang

Related authors

A long-term estimation of biogenic volatile organic compound (BVOC) emission in China from 2001–2016: the roles of land cover change and climate variability
Hui Wang, Qizhong Wu, Alex B. Guenther, Xiaochun Yang, Lanning Wang, Tang Xiao, Jie Li, Jinming Feng, Qi Xu, and Huaqiong Cheng
Atmos. Chem. Phys., 21, 4825–4848, https://doi.org/10.5194/acp-21-4825-2021,https://doi.org/10.5194/acp-21-4825-2021, 2021
Short summary
Sensitivity of biogenic volatile organic compound emissions to leaf area index and land cover in Beijing
Hui Wang, Qizhong Wu, Hongjun Liu, Yuanlin Wang, Huaqiong Cheng, Rongrong Wang, Lanning Wang, Han Xiao, and Xiaochun Yang
Atmos. Chem. Phys., 18, 9583–9596, https://doi.org/10.5194/acp-18-9583-2018,https://doi.org/10.5194/acp-18-9583-2018, 2018
Short summary
Summer ozone variation in North China based on satellite and site observations
Lihua Zhou, Jing Zhang, Hui Wang, Wenhao Xue, Xiaohui Zheng, and Siguang Zhu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-537,https://doi.org/10.5194/acp-2018-537, 2018
Preprint retracted
Short summary
GNAQPMS v1.1: accelerating the Global Nested Air Quality Prediction Modeling System (GNAQPMS) on Intel Xeon Phi processors
Hui Wang, Huansheng Chen, Qizhong Wu, Junmin Lin, Xueshun Chen, Xinwei Xie, Rongrong Wang, Xiao Tang, and Zifa Wang
Geosci. Model Dev., 10, 2891–2904, https://doi.org/10.5194/gmd-10-2891-2017,https://doi.org/10.5194/gmd-10-2891-2017, 2017
Short summary

Related subject area

Atmospheric sciences
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024,https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024,https://doi.org/10.5194/gmd-17-8773-2024, 2024
Short summary
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024,https://doi.org/10.5194/gmd-17-8639-2024, 2024
Short summary
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024,https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024,https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary

Cited articles

Chang, J. S., Brost, R. A., Isaksen, I. S. A., Madronich, S., Middleton, P., Stockwell, W. R., and Walcek, C. J.: A three-dimensional Eulerian acid deposition model: Physical concepts and formulation, J. Geophys. Res.-Atmos., 92, 14681–14700, 1987. 
Chen, H., Wang, Z., Qizhong, W. U., Jianbin, W. U., Yan, P., Tang, X., and Wang, Z.: Application of Air Quality Multi-Model Forecast System in Guangzhou: Model Description and Evaluation of PM10 Forecast Performance, Clim. Environ. Res., 18, 427–435, 2013. 
Chen, H. S., Wang, Z. F., Li, J., Tang, X., Ge, B. Z., Wu, X. L., Wild, O., and Carmichael, G. R.: GNAQPMS-Hg v1.0, a global nested atmospheric mercury transport model: model description, evaluation and application to trans-boundary transport of Chinese anthropogenic emissions, Geosci. Model Dev., 8, 2857–2876, https://doi.org/10.5194/gmd-8-2857-2015, 2015. 
Feng, F., Wang, Z., Li, J., and Carmichael, G. R.: A nonnegativity preserved efficient algorithm for atmospheric chemical kinetic equations, Appl. Mathe. Comput., 271, 519–531, 2015. 
Gao, M., Carmichael, G. R., Wang, Y., Saide, P. E., Yu, M., Xin, J., Liu, Z., and Wang, Z.: Modeling study of the 2010 regional haze event in the North China Plain, Atmos. Chem. Phys., 16, 1673–1691, https://doi.org/10.5194/acp-16-1673-2016, 2016. 
Download
Short summary
A new framework was designed for the widely used Carbon Bond Mechanism Z (CBM-Z) gas-phase chemical kinetics kernel to adapt the single-instruction, multiple-data (SIMD) technology in next-generation processors like Knights Landing (KNL) to improve their calculation performance. The optimization is aimed at implementing the fine-grain level parallelization of CBM-Z. The test results showed significant acceleration with our optimization on both CPU and KNL platforms.