科研成果

Developing highly scalable algorithms for global atmospheric modeling is becoming increasingly important as scientists inquire to understand behaviors of the global atmosphere at extreme scales. Nowadays, heterogeneous architecture based on both processors and accelerators is becoming an important solution for large-scale computing. However, large-scale simulation of the global atmosphere brings a severe challenge to the development of highly scalable algorithms that fit well into state-of-the-art heterogeneous systems. Although successes have been made on GPU-accelerated computing in some top-level applications, studies on fully exploiting heterogeneous architectures in global atmospheric modeling are still very less to be seen, due in large part to both the computational difficulties of the mathematical models and the requirement of high accuracy for long term simulations. In this paper, we propose a peta-scalable hybrid algorithm that is successfully applied in a cubed-sphere shallow-water model in global atmospheric simulations. We employ an adjustable partition between CPUs and GPUs to achieve a balanced utilization of the entire hybrid system, and present a pipe-flow scheme to conduct conflict-free inter-node communication on the cubed-sphere geometry and to maximize communication-computation overlap. Systematic optimizations for multithreading on both GPU and CPU sides are performed to enhance computing throughput and improve memory efficiency. Our experiments demonstrate nearly ideal strong and weak scalabilities on up to 3,750 nodes of the Tianhe-1A. The largest run sustains a performance of 0.8 Pflops in double precision (32% of the peak performance), using 45,000 CPU cores and 3,750 GPUs.

Brominated flame retardants (BFRs) are important persistent organic pollutants. Analysis of BFRs in atmospheric samples in a previous study led us to suspect the presence of unidentified organic bromides, other than polybrominated diphenyl ethers (PBDEs), in the atmosphere. In this study, we identified and quantified polybromobenzenes, a group of organic bromides, in air samples collected through passive sampling in gridded observations in North China. We investigated their concentrations and spatial distribution, and estimated the proportion due to different sources. We detected seven species of polybromobenzenes, including hexabromobenzene (HBB), pentabromotoluene (PBT), pentabromoethylbenzene (PBEB), pentabromobenzene (PeBB), tetrabromobenzenes (TeBBs), and tribromotoluene (TrBT), in all or most of the field samples, indicating widespread occurrence of this class of pollutants. The median concentrations of each pollutant ranged from 20.0 to 144 pg/sample (or from 0.07 to 1.16 pg/m(3)), with relatively high concentrations found near e-waste recycling sites, BFR manufacturing sites, and areas of high population density. Positive matrix factorization (PMF) analysis revealed that similar to 70% of HBB, PBT, PBEB, and PeBB was from commercial products, while similar to 80% of 1,2,3,S-TeBB, 1,2,4,S-TeBB, and 2,4,5-TrBT was linked with BFR manufacturing. This study provides essential information on widespread polybromobenzene pollutants in the atmosphere, particularly TeBBs and TrBT, for which this is the first report of their presence as atmospheric pollutants.