Parallelization and I/O performance optimization of a global nonhydrostatic dynamical core using MPI

The Global ‐ Regional Integrated forecast SysTem (GRIST) is the next- generation weather and climate integrated model dynamic framework developed by Chinese Academy of Meteorological Sciences. In this paper, we present several changes made to the global nonhydrostatic dynamical (GND) core, which is part of the ongoing prototype of GRIST. The changes leveraging MPI and PnetCDF techniques were targeted at the parallelization and performance optimization to the original serial GND core. Meanwhile, some sophisticated data structures and interfaces were designed to adjust flexibly the size of boundary and halo domains according to the variable accuracy in parallel context. In addition, the I/O performance of PnetCDF decreases as the number of MPI processes increases in our experimental environment. Especially when the number exceeds 6000, it caused system-wide outages (SWO). Thus, a grouping solution was proposed to overcome that issue. Several experiments were carried out on the supercomputing platform based on Intel x86 CPUs in the National Supercomputing Center in Wuxi. The results demonstrated that the parallel GND core based on grouping solution achieves good strong scalability and improves the performance significantly, as well as avoiding the SWOs

Multi-decadal trends in global terrestrial evapotranspiration and its components

Evapotranspiration (ET) is the process by which liquid water becomes water vapor and energetically this accounts for much of incoming solar radiation. If this ET did not occur temperatures would be higher, so understanding ET trends is crucial to predict future temperatures. Recent studies have reported prolonged declines in ET in recent decades, although these declines may relate to climate variability. Here, we used a well-validated diagnostic model to estimate daily ET during 1981–2012, and its three components: transpiration from vegetation (Et), direct evaporation from the soil (Es) and vaporization of intercepted rainfall from vegetation (Ei). During this period, ET over land has increased significantly (p < 0.01), caused by increases in Et and Ei, which are partially counteracted by Es decreasing. These contrasting trends are primarily driven by increases in vegetation leaf area index, dominated by greening. The overall increase in Et over land is about twofold of the decrease in Es. These opposing trends are not simulated by most Coupled Model Intercomparison Project phase 5 (CMIP5) models, and highlight the importance of realistically representing vegetation changes in earth system models for predicting future changes in the energy and water cycle

Semiconducting nonperovskite ferroelectric oxynitride designed ab initio

Recent discovery of HfO2-based and nitride-based ferroelectrics that are compatible to the semiconductor manufacturing process have revitalized the field of ferroelectric-based nanoelectronics. Guided by a simple design principle of charge compensation and density functional theory calculations, we discover HfO2-like mixed-anion materials, TaON and NbON, can crystallize in the polar Pca21 phase with a strong thermodynamic driving force to adopt anion ordering spontaneously. Both oxynitrides possess large remnant polarization, low switching barriers, and unconventional negative piezoelectric effect, making them promising piezoelectrics and ferroelectrics. Distinct from HfO2 that has a wide band gap, both TaON and NbON can absorb visible light and have high charge carrier mobilities, suitable for ferroelectric photovoltaic and photocatalytic applications. This new class of multifunctional nonperovskite oxynitride containing economical and environmentally benign elements offer a platform to design and optimize high-performing ferroelectric semiconductors for integrated systems

Binding affinity-based intracellular drug detection enabled by a unimolecular cucurbit[7]uril-dye conjugate

Label-free fluorescence-based chemosensing has been increasingly brought into focus due to its simplicity and high sensitivity for intracellular monitoring of molecules. Currently used methods, such as conventional indicator displacement assays (IDAs), pose limitations related to dissociation upon dilution, random diffusion of the released indicators, and high sensitivity to interference by agents from the ambient cellular environment (e.g., salts, enzymes, and proteins). Herein we report a potentially widely applicable strategy to overcome the limitations of conventional IDAs by employing a macrocyclic cucurbit[7]uril (CB7) host covalently coupled to a nitrobenzoxadiazole (NBD) fluorescent dye (CB7-NBD conjugate). As a proof of concept, we demonstrated that the CB7-NBD unimolecular conjugate responded to various target analytes even in the complex live cell system. Moreover, the sensing system was compatible with fluorescence imaging, fluorescence-assisted cell sorting (FACS), and fluorescence spectrometry with a microplate reader. These experiments demonstrated an application of covalently bound unimolecular CB7-NBD conjugate as a sensor for detecting diverse analytes in the intracellular compartment of live cells

A Modular Framework of Distributed Hydrological Modeling System: Hydroinformatic Modeling System, HIMS

Distributed hydrological models have been shown high light on because of the spatial variability of hydrological processes. On the other hand, the complexity of the hydrological processes, the multi-purposes of hydrological modeling and the availability of observed data have made it difficult to bring forward a hydrological model system for general use. It is always confused and time consumed to find a model of most fit to practical application because of the variety types of hydrological models. In this paper, the framework of a modular based distributed hydrological modeling system has been discussed. The system was so called Hydroinformatic Modeling System (HIMS), include hydroinformatic management system, data pre- and post-processing system, and hydrological model & function library. For the management and processing of spatial information, basic GIS functions have been integrated into system on the basis of SUPERMAP, which is component based GIS software. The hydrological function library (HFL), which represents different processes of hydrological cycle, was the core of the entire system. Distributed hydrological models of different scale were all established on the HFL. The HIMS has been applied to hydrological research in the Yellow River Basin and has reached to some success. However, since it is still in its trial version, much more work need to be done to improve it

ShadowNet: A Secure and Efficient System for On-device Model Inference

With the increased usage of AI accelerators on mobile and edge devices, on-device machine learning (ML) is gaining popularity. Consequently, thousands of proprietary ML models are being deployed on billions of untrusted devices. This raises serious security concerns about model privacy. However, protecting the model privacy without losing access to the AI accelerators is a challenging problem. In this paper, we present a novel on-device model inference system, ShadowNet. ShadowNet protects the model privacy with Trusted Execution Environment (TEE) while securely outsourcing the heavy linear layers of the model to the untrusted hardware accelerators. ShadowNet achieves this by transforming the weights of the linear layers before outsourcing them and restoring the results inside the TEE. The nonlinear layers are also kept secure inside the TEE. The transformation of the weights and the restoration of the results are designed in a way that can be implemented efficiently. We have built a ShadowNet prototype based on TensorFlow Lite and applied it on four popular CNNs, namely, MobileNets, ResNet-44, AlexNet and MiniVGG. Our evaluation shows that ShadowNet achieves strong security guarantees with reasonable performance, offering a practical solution for secure on-device model inference.Comment: single column, 21 pages (29 pages include appendix), 12 figure