An assessment of the subduction rate in the CMIP6 historical experiment

Subduction process is a dynamical bridge for the exchanges of heat between the atmosphere and subsurface ocean water,which is regarded as a central proxy for the ocean climate studies.Given its key indicator in climate signals,it is of importance to examine the ability of a model to simulate the global subduction rate before investigating the climate dynamics.In this paper,we evaluated the ability of 21 climate models from Coupled Model Intercomparison Project Phase 6(CMIP6)in simulating the subduction rate.In general,the simulation ability of the models to the subduction climatology is better than that to the long-term variation trend.Based on the comprehensive analysis of climatology distribution and long-term trend of the subduction rate,GISS-E2-1-G performs better in reproducing the subduction rate climatology and IPSL-CM6A-LR can simulate positive long-term trend for both the global mean subduction rate and the lateral induction term in the Antarctic Circumpolar Current(ACC)region.However,it is still challenging to capture both the distribution characteristics of the subduction climatology and the long-term temporal trend for the 21 CMIP6 models.In addition,the model results demonstrate that,the ACC area is the major region contributing to the long-term trend of the global mean subduction rate.The analysis in this paper indicates that the poor simulation ability of reproducing the long-term trend of global mean subduction rate might be attributed to the ocean dynamics,for example,the zonal velocity at the bottom mixed layer and zonal gradient of mixed layer depth.

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.

Anonymous data collection scheme for cloud-aided mobile edge networks

With the rapid spread of smart sensors,data collection is becoming more and more important in Mobile Edge Networks(MENs).The collected data can be used in many applications based on the analysis results of these data by cloud computing.Nowadays,data collection schemes have been widely studied by researchers.However,most of the researches take the amount of collected data into consideration without thinking about the problem of privacy leakage of the collected data.In this paper,we propose an energy-efficient and anonymous data collection scheme for MENs to keep a balance between energy consumption and data privacy,in which the privacy information of senors is hidden during data communication.In addition,the residual energy of nodes is taken into consideration in this scheme in particular when it comes to the selection of the relay node.The security analysis shows that no privacy information of the source node and relay node is leaked to attackers.Moreover,the simulation results demonstrate that the proposed scheme is better than other schemes in aspects of lifetime and energy consumption.At the end of the simulation part,we present a qualitative analysis for the proposed scheme and some conventional protocols.It is noteworthy that the proposed scheme outperforms the existing protocols in terms of the above indicators.

生物大分子的量子计算模拟:并行量子算法的初步探索

Quantum computing is a rapidly-emerging technology that is widely expected to solve valuable problems in physics and chemistry.After quantum computational advantage in the task of sampling has been demonstrated on both photonic and superconductor quantum platforms[1,2],quantum computing is urgently seeking to solve problems of practical interest that are often intractable or at least computationally demanding for classical computers[3].

Stable classi?cation with limited sample: transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017

As the world strives to reduce the impact of population growth, urbanization, agricultural expansion, and climate change on food security, energy and water shortage, resource over-exploration, biodiversity loss, environmental pollution, and ultimately human health, timely and higher resolution land cover information is urgently needed to achieve the sustainable development goals of the United Nations.

Lessons Learned from Optimizing the Sunway Storage System for Higher Application I/O Performance

It is hard for applications to make full utilization of the peak bandwidth of the storage system in highperformance computers because of I/O interferences,storage resource misallocations and complex long I/O paths.We performed several studies to bridge this gap in the Sunway storage system,which serves the supercomputer Sunway TaihuLight.To locate these issues and connections between them,an end-to-end performance monitoring and diagnosis tool was developed to understand I/O behaviors of applications and the system.With the help of the tool,we were about to find out the root causes of such performance barriers at the I/O forwarding layer and the parallel file system layer.An application-aware I/O forwarding allocation framework was used to address the I/O interferences and resource misallocations at the I/O forwarding layer.A performance-aware data placement mechanism was proposed to mitigate the impact of I/O interferences and performance variations of storage devices in the PFS.Together,applications obtained much better I/O performance.During the process,we also proposed a lightweight storage stack to shorten the I/O path of applications with N-N I/O pattern.This paper summarizes these studies and presents the lessons learned from the process.

SCStore： Managing Scientific Computing Packages for Hybrid System with Containers

Managing software packages in a scientific computing environment is a challenging task, especially in the case of heterogeneous systems. It is error prone when installing and updating software packages in a sophisticated computing environment. Testing and performance evaluation in an on-the-fly manner is also a troublesome task for a production system. In this paper, we discuss a package management scheme based on containers. The newly developed method can ease the maintenance complexity and reduce human mistakes. We can benefit from the self-containing and isolation features of container technologies for maintaining the software packages among intricately connected clusters. By deploying the Super Computing application Strore（SCStore） over the WAN connected world-largest clusters, it proved that it can greatly reduce the effort for maintaining the consistency of software environment and bring benefit to achieve automation.

Understanding the Performance of an Unstructured-Mesh Global Shallow Water Model on Kinetic Energy Spectra and Nonlinear Vorticity Dynamics

A strategy for evaluating a global shallow water model based on aspects of kinetic energy spectra and nonlinear vorticity dynamics is proposed in this study.The kinetic energy spectra and nonlinear vorticity dynamics of a recently developed global shallow water model on an unstructured mesh are evaluated in comparison with the benchmark solutions from a global high-resolution spectral model.The results show that the kinetic energy spectra,the rotational and divergent components,the stationary and transient components,and the nonlinear spectral fluxes of the developed shallow water model agree well with those generated by the reference model.In addition,the influence of different flux operators for transporting the potential vorticity(PV)is assessed specifically.It is indicated that the second-order flux operator leads to a spurious increase in the kinetic energy at the tail of the spectrum,whereas the upwind third-order flux operator does not support this behavior owing to implicit numerical diffusion.Moreover,the nonlinear vorticity dynamics is studied by using colliding modons.It is found that the grid-point model maintains the symmetrical pattern of vortices,and generates similar kinetic energy spectra and nonlinear spectral fluxes to the reference model.The evaluation provides a reference for assessing the shallow water model in terms of nonlinear dynamics,and the developed global shallow water model presents a good example.

E级超算下应用软件发展的挑战与趋势（英文）

在未来三到五年,多台百亿亿次超级计算机系统将在全球多个国家部署。面对前所未有的超强计算能力与超大并行规模,如何设计和实现相匹配的应用软件,成为当前高性能计算软件发展的重要挑战。以中国神威太湖之光超级计算机系统(峰值计算能力12.5亿亿次)及其相关应用挑战和解决方案为出发点,根据我们目前的经验,讨论未来十年全球超级计算机的软硬件发展方向,并提出未来高性能计算应用软件开发中将会遇到的潜在挑战和可能的发展趋势。