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A review of high performance computing applications in high-speed rail systems 认领 引用 被引量：4
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作者 Shenyuan Ren Yidong Li 《High-Speed Railway》 2023年第2期92-96,共5页
Further improving the railway innovation capacity and technological strength is the important goal of the 14th Five-Year Plan for railway scientific and technological innovation.It includes promoting the deep integrat... Further improving the railway innovation capacity and technological strength is the important goal of the 14th Five-Year Plan for railway scientific and technological innovation.It includes promoting the deep integration of cutting-edge technologies with the railway systems,strengthening the research and application of intelligent railway technologies,applying green computing technologies and advancing the collaborative sharing of transportation big data.The high-speed rail system tasks need to process huge amounts of data and heavy workload with the requirement of ultra-fast response.Therefore,it is of great necessity to promote computation efficiency by applying High Performance Computing(HPC)to high-speed rail systems.The HPC technique is a great solution for improving the performance,efficiency,and safety of high-speed rail systems.In this review,we introduce and analyze the application research of high performance computing technology in the field of highspeed railways.These HPC applications are cataloged into four broad categories,namely:fault diagnosis,network and communication,management system,and simulations.Moreover,challenges and issues to be addressed are discussed and further directions are suggested. 展开更多
关键词 High performance computing High-speed rail
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The Changing Face of High Performance Computing in the United States 认领 引用 被引量：2
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作者 Ann Haves 《Wuhan University Journal of Natural Sciences》 CAS 1996年第Z1期309-311,共3页
TheChangingFaceofHighPerformanceComputingintheUnitedStatesAnnHaves（AdvancedComputingLaboratoryLosAlamosNationalLaboratoryLosA...
关键词 The Changing Face of High Performance Computing in the United States
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Optimization of fault tolerance for iterative graph algorithm in spark GraphX based on high performance computing cluster 认领 引用
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作者 Mengsi He Zhongming Fu Wenlong Tian 《CCF Transactions on High Performance Computing》 EI CSCD 2025年第5期465-477,共13页
GraphX is a graph computing library based on Spark systems,where fault tolerance is a necessary guarantee for the high availability.However,the existing fault tolerance methods are mostly implemented in a pessimistic ... GraphX is a graph computing library based on Spark systems,where fault tolerance is a necessary guarantee for the high availability.However,the existing fault tolerance methods are mostly implemented in a pessimistic way and are aimed at general computing tasks.Considering the characteristics of iterative computation,this paper presents a combination method of the optimistic fault tolerance and checkpoint for recovering the data under different failure conditions.Firstly,for single node failure,we propose the optimistic fault tolerance mechanism based on compensation function.It does not add fault tolerance measures in advance and will not incur additional costs when there are no failures.Secondly,for multiple node failures,we propose the automatic checkpoint management strategy based on RDD importance.It comprehensively considers the factors of lineage length of RDD,dependency relationship,and computation time of RDD,which can set the RDD as the checkpoint properly.Finally,we implement our proposals in GraphX of Spark−3.5.1,and evaluate the performance by using representative iterative graph algorithms on the high performance computing cluster.The results verify the correctness of iteration results of the mechanism,and illustrate that when recovering the RDD partition,the job execution time can be reduced by the mechanism and strategy substantially. 展开更多
关键词 Fault tolerance Iterative graph algorithm Spark GraphX High performance computing
High performance computing of DGDFT for tens of thousands of atoms using millions of cores on Sunway TaihuLight 认领 引用 被引量：11
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作者 Wei Hu Xinming Qin +9 位作者 Qingcai Jiang Junshi Chen Hong An Weile Jia Fang Li Xin Liu Dexun Chen Fangfang Liu Yuwen Zhao Jinlong Yang 《Science Bulletin》 SCIE EI CAS CSCD 2021年第2期111-119,M0003,共9页
High performance computing(HPC)is a powerful tool to accelerate the Kohn–Sham density functional theory(KS-DFT)calculations on modern heterogeneous supercomputers.Here,we describe a massively parallel implementation ... High performance computing(HPC)is a powerful tool to accelerate the Kohn–Sham density functional theory(KS-DFT)calculations on modern heterogeneous supercomputers.Here,we describe a massively parallel implementation of discontinuous Galerkin density functional theory(DGDFT)method on the Sunway Taihu Light supercomputer.The DGDFT method uses the adaptive local basis(ALB)functions generated on-the-fly during the self-consistent field(SCF)iteration to solve the KS equations with high precision comparable to plane-wave basis set.In particular,the DGDFT method adopts a two-level parallelization strategy that deals with various types of data distribution,task scheduling,and data communication schemes,and combines with the master–slave multi-thread heterogeneous parallelism of SW26010 processor,resulting in large-scale HPC KS-DFT calculations on the Sunway Taihu Light supercomputer.We show that the DGDFT method can scale up to 8,519,680 processing cores(131,072 core groups)on the Sunway Taihu Light supercomputer for studying the electronic structures of twodimensional(2 D)metallic graphene systems that contain tens of thousands of carbon atoms. 展开更多
关键词 Density functional theory Tens of thousands of atoms High performance computing Sunway TaihuLight
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AceMesh:a structured data driven programming language for high performance computing 认领 引用 被引量：4
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作者 Li Chen Shenglin Tang +3 位作者 You Fu Xiran Gao Jie Guo Shangzhi Jiang 《CCF Transactions on High Performance Computing》 EI 2020年第4期309-322,共14页
Asynchronous task-based programming models are gaining popularity to address the programmability and performance challenges of contemporary large scale high performance computing systems.In this paper we present AceMe... Asynchronous task-based programming models are gaining popularity to address the programmability and performance challenges of contemporary large scale high performance computing systems.In this paper we present AceMesh,a taskbased,data-driven language extension targeting legacy MPI applications.Its language features include data-centric parallelizing template,aggregated task dependence for parallel loops.These features not only relieve the programmer from tedious refactoring details but also provide possibility for structured execution of complex task graphs,data locality exploitation upon data tile templates,and reducing system complexity incurred by complex array sections.We present the prototype implementation,including task shifting,data management and communication-related analysis and transformations.The language extension is evaluated on two supercomputing platforms.We compare the performance of AceMesh with existing programming models,and the results show that NPB/MG achieves at most 1.2X and 1.85X speedups on TaihuLight and TH-2,respectively,and the Tend_lin benchmark attains more than 2X speedup on average and attain at most 3.0X and 2.2X speedups on the two platforms,respectively. 展开更多
关键词 High performance computing Programming model MPI Task parallel Data driven Task dependence
Applications and challenges of high performance computing in genomics 认领 引用 被引量：2
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作者 Meiye Jiang Congfan Bu +2 位作者 Jingyao Zeng Zhenglin Du Jingfa Xiao 《CCF Transactions on High Performance Computing》 EI 2021年第4期344-352,共9页
With the rapid development of high-throughput sequencing technologies,the scale of sequencing data continuously increases at unprecedented speed.In the field of genomics,high performance computing(HPC)is urgently need... With the rapid development of high-throughput sequencing technologies,the scale of sequencing data continuously increases at unprecedented speed.In the field of genomics,high performance computing(HPC)is urgently needed to process these large-scale sequencing data,which uses supercomputers and parallel processing technologies to solve complex computing problems and performs intensive computing operations across massive resources.Nowadays,high performance computing plays an important role in data-driven sciences,and is widely used in genomics research.However,while dealing with massive multi-dimensional genomics data using high performance computing,there are still many challenges which limit the wide applications of HPC,such as high data complexity,huge memory requirements and low parallel computing performance.In this paper,we reviewed the irreplaceable applications of high performance computing in genomics,especially in pangenome,single-cell transcriptome and large-scale population sequencing studies.In future,with the developing methods of hardware acceleration and algorithm optimization,the applications of high performance computing will be more inseparable in complex and large-scale genomics studies. 展开更多
关键词 Genomics High performance computing Pan-genome Single-cell transcriptome Large-scale population sequencing
Monte Carlo performance study of virtual high performance computing cluster over cloud 认领 引用
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作者 Libing Zhu Ze Xi +5 位作者 Peng Cong Gongyi Yu Yuan Liu Xincheng Xiang Wei Xu Xiangang Wang 《Radiation Medicine and Protection》 CSCD 2022年第3期108-114,共7页
Objective:As a high computation cost discipline,nuclear science and engineering still relies heavily on traditional high performance computing(HPC)clusters.However,the usage of traditional HPC for nuclear science and ... Objective:As a high computation cost discipline,nuclear science and engineering still relies heavily on traditional high performance computing(HPC)clusters.However,the usage of traditional HPC for nuclear science and engineering has been limited due to the poor flexibility,the software compatibility and the poor user interfaces.Virtualized/virtual HPC(vHPC)can mimic an HPC by using a cloud computing platform.In this work,we designed and developed a vHPC system for employment in nuclear engineering.Methods:The system is tested using the computation of the numberπby Monte Carlo and an X-ray digital imaging system simulation.The performance of the vHPC system is compared with that of the traditional HPCs.Results:As the number of the simulated particles increases,the virtual cluster computing time grows propor-tionally.The time used for the simulation of the X-ray imaging was about 21.1 h over a 12 kernels virtual server.Experimental results show that the performance of virtual cluster computing and the actual physical machine is almost the same.Conclusions:From these tests,it is concluded that vHPC is a good alternative for employing in nuclear engineering.The proposed vHPC in this paper will make HPC flexible and easy to deploy. 展开更多
关键词 Cloud computing Virtualization High performance computing(HPC) Virtual HPC Monte Carlo
High performance computing for first‑principles Kohn‑Sham density functional theory towards exascale supercomputers 认领 引用
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作者 Xinming Qin Junshi Chen +8 位作者 Zhaolong Luo Lingyun Wan Jielan Li Shizhe Jiao Zhenlin Zhang Qingcai Jiang Wei Hu Hong An Jinlong Yang 《CCF Transactions on High Performance Computing》 EI 2023年第1期26-42,共17页
High performance computing(HPC)plays an essential role in enabling first-principles calculations based on the Kohn–Sham density functional theory(KS-DFT)for investigating quantum structural and electronic properties ... High performance computing(HPC)plays an essential role in enabling first-principles calculations based on the Kohn–Sham density functional theory(KS-DFT)for investigating quantum structural and electronic properties of large-scale molecules and solids in condensed matter physics,quantum chemistry and materials science.This review focuses on recent advances for HPC software development in large-scale KS-DFT calculations containing tens of thousands of atoms on modern heterogeneous supercomputers,especially for the HPC software with independent intellectual property rights supported on the Chinese domestic exascale supercomputers.We first introduce three various types of DFT software developed on modern heterogeneous supercomputers,involving PWDFT(Plane-Wave Density Functional Theory),HONPAS(Hefei Order-N Packages for Ab initio Simulations)and DGDFT(Discontinuous Galerkin Density Functional Theory),respectively based on three different types of basis sets(plane waves,numerical atomic orbitals and adaptive local basis functions).Then,we describe the theoretical algorithms and parallel implementation of these three software on modern heterogeneous supercomputers in detail.Finally,we conclude this review and propose several promising research fields for future large-scale KS-DFT calculations towards exascale supercomputers. 展开更多
关键词 First-principles calculations Density functional theory Software development High performance computing Exascale supercomputers
Editorial for the special issue on new algorithms and software for E‑scale high performance computing 认领 引用
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作者 Jiachang Sun Huiyuan Li Wenjing Ma 《CCF Transactions on High Performance Computing》 EI 2023年第1期1-2,共2页
As a great power in supporting scientific research,engineering,and many other fields,High Performance Computing plays a more and more important role is the current world.Supercomputers are deployed in many countries a... As a great power in supporting scientific research,engineering,and many other fields,High Performance Computing plays a more and more important role is the current world.Supercomputers are deployed in many countries around the world,and have been used in a wide range of areas.Technology of designing,building,managing,and utilizing high performance computers has been developing dramatically.With the debut of Frontier in ORNL,the world has stepped into the Exascale era. 展开更多
关键词 performance computing algorithm supercomputers high performance computers exascale era high performance computing scientific research engineering
Self-deployed execution environment for high performance computing 认领 引用 被引量：2
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作者 Mingtian SHAO Kai LU Wenzhe ZHANG 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2022年第6期845-857,共13页
Traditional high performance computing(HPC)systems provide a standard preset environment to support scientific computation.However,HPC development needs to provide support for more and more diverse applications,such a... Traditional high performance computing(HPC)systems provide a standard preset environment to support scientific computation.However,HPC development needs to provide support for more and more diverse applications,such as artificial intelligence and big data.The standard preset environment can no longer meet these diverse requirements.If users still run these emerging applications on HPC systems,they need to manually maintain the specific dependencies(libraries,environment variables,and so on)of their applications.This increases the development and deployment burden for users.Moreover,the multi-user mode brings about privacy problems among users.Containers like Docker and Singularity can encapsulate the job’s execution environment,but in a highly customized HPC system,cross-environment application deployment of Docker and Singularity is limited.The introduction of container images also imposes a maintenance burden on system administrators.Facing the above-mentioned problems,in this paper we propose a self-deployed execution environment(SDEE)for HPC.SDEE combines the advantages of traditional virtualization and modern containers.SDEE provides an isolated and customizable environment(similar to a virtual machine)to the user.The user is the root user in this environment.The user develops and debugs the application and deploys its special dependencies in this environment.Then the user can load the job to compute nodes directly through the traditional HPC job management system.The job and its dependencies are analyzed,packaged,deployed,and executed automatically.This process enables transparent and rapid job deployment,which not only reduces the burden on users,but also protects user privacy.Experiments show that the overhead introduced by SDEE is negligible and lower than those of both Docker and Singularity. 展开更多
关键词 Execution environment High performance computing Light-weight Isolation Overlay
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Trends and advanced techniques in high-speed simultaneous bi-directional transceivers for die-to-die interfaces 认领 引用
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作者 Yufeng Ge Ziqi Xue +5 位作者 Xuanyu Li Aoxuan Wen Hongzhi Wu Pingyi Cai Xuxu Cheng Quan Pan 《Journal of Semiconductors》 EI CAS CSCD 2026年第7期18-23,共6页
The rapid proliferation of AI and high-performance computing(HPC)applications is driving chip-to-chip and die-todie(D2D)interfaces toward substantially higher bandwidth density.These high-speed interface technologies ... The rapid proliferation of AI and high-performance computing(HPC)applications is driving chip-to-chip and die-todie(D2D)interfaces toward substantially higher bandwidth density.These high-speed interface technologies are essential for chiplet architectures,high-bandwidth memory(HBM),and heterogeneous integrated systems.Single-ended simultaneous bidirectional(SBD)technology doubles system throughput by enabling concurrent transmission and reception over a single physical channel. 展开更多
关键词 high performance computing interface technologies heterogeneous integrated systemssingle ended chiplet architectureshigh bandwidth AI die die interfaces chip chip concurrent transmission reception
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Scalable parallel evolutionary optimization on high performance computing 认领 引用
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作者 Chen Jin Daren Zheng +2 位作者 Shuke He Ao Cheng Gang Liu 《Aerospace Traffic and Safety》 2024年第2期93-102,共10页
To improve the efficiency of evolutionary algorithms(EAs)for solving complex problems with large populations,this paper proposes a scalable parallel evolution optimization(SPEO)framework with an elastic asynchronous m... To improve the efficiency of evolutionary algorithms(EAs)for solving complex problems with large populations,this paper proposes a scalable parallel evolution optimization(SPEO)framework with an elastic asynchronous migration(EAM)mechanism.SPEO addresses two main challenges that arise in large-scale parallel EAs:(1)heavy communication workload from extensive information exchange across numerous processors,which reduces computational efficiency,and(2)loss of population diversity due to similar solutions generated and shared by many processors.The EAM mechanism introduces a self-adaptive communication scheme to mitigate communication overhead,while a diversity-preserving buffer helps maintain diversity by filtering similar solutions.Experimental results on eight CEC2014 benchmark functions using up to 512 CPU cores on the Australian National Computational Infrastructure(NCI)platform demonstrate that SPEO not only scales efficiently with an increasing number of processors but also achieves improved solution quality compared to state-of-the-art island-based EAs. 展开更多
关键词 Parallel evolutionary algorithm High performance computing(HPC) Computational efficiency Asynchronous migration
Computing over Space:Status,Challenges,and Opportunities 认领 引用 被引量：8
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作者 Yaoqi Liu Yinhe Han +3 位作者 Hongxin Li Shuhao Gu Jibing Qiu Ting Li 《Engineering》 SCIE EI CSCD 2025年第11期20-25,共6页
1.Introduction The rapid expansion of satellite constellations in recent years has resulted in the generation of massive amounts of data.This surge in data,coupled with diverse application scenarios,underscores the es... 1.Introduction The rapid expansion of satellite constellations in recent years has resulted in the generation of massive amounts of data.This surge in data,coupled with diverse application scenarios,underscores the escalating demand for high-performance computing over space.Computing over space entails the deployment of computational resources on platforms such as satellites to process large-scale data under constraints such as high radiation exposure,restricted power consumption,and minimized weight. 展开更多
关键词 satellite constellations deployment computational resources data processing space computing radiation exposure space high performance computing power consumption
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A NEW HIGH PERFORMANCE SPARSE STATIC SOLVER IN FINITE ELEMENT ANALYSIS WITH LOOP-UNROLLING 认领 引用 被引量：1
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作者 Chen Pu Sun Shuli 《Acta Mechanica Solida Sinica》 SCIE EI 2005年第3期248-255,共8页
In the previous papers, a high performance sparse static solver with two-level unrolling based on a cell-sparse storage scheme was reported. Although the solver reaches quite a high efficiency for a big percentage of ... In the previous papers, a high performance sparse static solver with two-level unrolling based on a cell-sparse storage scheme was reported. Although the solver reaches quite a high efficiency for a big percentage of finite element analysis benchmark tests, the MFLOPS （million floating operations per second） of LDL^T factorization of benchmark tests vary on a Dell Pentium IV 850 MHz machine from 100 to 456 depending on the average size of the super-equations, i.e., on the average depth of unrolling. In this paper, a new sparse static solver with two-level unrolling that employs the concept of master-equations and searches for an appropriate depths of unrolling is proposed. The new solver provides higher MFLOPS for LDL^T factorization of benchmark tests, and therefore speeds up the solution process. 展开更多
关键词 high performance computing sparse matrix finite element analysis
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Parallel Optical Interconnect Technology:Combination of Higher Performance and Lower Energy Consumption 认领 引用
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作者 Qiao Yaojun Gu Rentao Ji Yuefeng 《China Communications》 SCIE 2010年第3期99-106,共8页
This paper analyzes the physical potential,computing performance benefi t and power consumption of optical interconnects.Compared with electrical interconnections,optical ones show undoubted advantages based on physic... This paper analyzes the physical potential,computing performance benefi t and power consumption of optical interconnects.Compared with electrical interconnections,optical ones show undoubted advantages based on physical factor analysis.At the same time,since the recent developments drive us to think about whether these optical interconnect technologies with higher bandwidth but higher cost are worthy to be deployed,the computing performance comparison is performed.To meet the increasing demand of large-scale parallel or multi-processor computing tasks,an analytic method to evaluate parallel computing performance ofinterconnect systems is proposed in this paper.Both bandwidth-limit model and full-bandwidth model are under our investigation.Speedup and effi ciency are selected to represent the parallel performance of an interconnect system.Deploying the proposed models,we depict the performance gap between the optical and electrically interconnected systems.Another investigation on power consumption of commercial products showed that if the parallel interconnections are deployed,the unit power consumption will be reduced.Therefore,from the analysis of computing influence and power dissipation,we found that parallel optical interconnect is valuable combination of high performance and low energy consumption.Considering the possible data center under construction,huge power could be saved if parallel optical interconnects technologies are used. 展开更多
关键词 optical interconnects high performance computing power dissipation
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HIGH PERFORMANCE SPARSE SOLVER FOR UNSYMMETRICAL LINEAR EQUATIONS WITH OUT-OF-CORE STRATEGIES AND ITS APPLICATION ON MESHLESS METHODS 认领 引用 被引量：1
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作者 苑维然 陈璞 刘凯欣 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2006年第10期1339-1348,共10页
A new direct method for solving unsymmetrical sparse linear systems（USLS） arising from meshless methods was introduced. Computation of certain meshless methods such as meshless local Petrov-Galerkin （MLPG） method ... A new direct method for solving unsymmetrical sparse linear systems（USLS） arising from meshless methods was introduced. Computation of certain meshless methods such as meshless local Petrov-Galerkin （MLPG） method need to solve large USLS. The proposed solution method for unsymmetrical case performs factorization processes symmetrically on the upper and lower triangular portion of matrix, which differs from previous work based on general unsymmetrical process, and attains higher performance. It is shown that the solution algorithm for USLS can be simply derived from the existing approaches for the symmetrical case. The new matrix factorization algorithm in our method can be implemented easily by modifying a standard JKI symmetrical matrix factorization code. Multi-blocked out-of-core strategies were also developed to expand the solution scale. The approach convincingly increases the speed of the solution process, which is demonstrated with the numerical tests. 展开更多
关键词 sparse matrices linear equations meshless methods high performance computation
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Computing for power system operation and planning: Then, now, and the future 认领 引用
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作者 Yousu Chen Zhenyu Huang +1 位作者 Shuangshuang Jin Ang Li 《iEnergy》 2022年第3期315-324,共10页
With the global trend of pursuing clean energy and decarbonization,power systems have been evolving in a fast pace that we have never seen in the history of electrification.This evolution makes the power system more d... With the global trend of pursuing clean energy and decarbonization,power systems have been evolving in a fast pace that we have never seen in the history of electrification.This evolution makes the power system more dynamic and more distributed,with higher uncertainty.These new power system behaviors bring significant challenges in power system modeling and simulation as more data need to be analyzed for larger systems and more complex models to be solved in a shorter time period.The conventional computing approaches will not be sufficient for future power systems.This paper provides a historical review of computing for power system operation and planning,discusses technology advancements in high performance computing(HPC),and describes the drivers for employing HPC techniques.Some high performance computing application examples with different HPC techniques,including the latest quantum computing,are also presented to show how HPC techniques can help us be well prepared to meet the requirements of power system computing in a clean energy future. 展开更多
关键词 Power system computing high performance computing quantum computing contingency analysis state estimation dynamic simulation machine learning optimization exascale computing.
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High Throughput Scheduling Algorithms for Input Queued Packet Switches 认领 引用 被引量：4
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作者 R.Chithra Devi D.Jemi Florinabel Narayanan Prasanth 《Computers, Materials & Continua》 SCIE EI 2022年第1期1527-1540,共14页
The high-performance computing paradigm needs high-speed switching fabrics to meet the heavy traffic generated by their applications.These switching fabrics are efficiently driven by the deployed scheduling algorithms... The high-performance computing paradigm needs high-speed switching fabrics to meet the heavy traffic generated by their applications.These switching fabrics are efficiently driven by the deployed scheduling algorithms.In this paper,we proposed two scheduling algorithms for input queued switches whose operations are based on ranking procedures.At first,we proposed a Simple 2-Bit(S2B)scheme which uses binary ranking procedure and queue size for scheduling the packets.Here,the Virtual Output Queue(VOQ)set with maximum number of empty queues receives higher rank than other VOQ’s.Through simulation,we showed S2B has better throughput performance than Highest Ranking First(HRF)arbitration under uniform,and non-uniform traffic patterns.To further improve the throughput-delay performance,an Enhanced 2-Bit(E2B)approach is proposed.This approach adopts an integer representation for rank,which is the number of empty queues in a VOQ set.The simulation result shows E2B outperforms S2B and HRF scheduling algorithms with maximum throughput-delay performance.Furthermore,the algorithms are simulated under hotspot traffic and E2B proves to be more efficient. 展开更多
关键词 Crossbar switch input queued switch virtual output queue scheduling algorithm high performance computing
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Techniques,Tricks,and Algorithms for Efficient GPU-Based Processing of Higher Order Hyperbolic PDEs 认领 引用
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作者 Sethupathy Subramanian Dinshaw S.Balsara +1 位作者 Deepak Bhoriya Harish Kumar 《Communications on Applied Mathematics and Computation》 EI 2024年第4期2336-2384,共49页
GPU computing is expected to play an integral part in all modern Exascale supercomputers.It is also expected that higher order Godunov schemes will make up about a significant fraction of the application mix on such s... GPU computing is expected to play an integral part in all modern Exascale supercomputers.It is also expected that higher order Godunov schemes will make up about a significant fraction of the application mix on such supercomputers.It is,therefore,very important to prepare the community of users of higher order schemes for hyperbolic PDEs for this emerging opportunity.Not every algorithm that is used in the space-time update of the solution of hyperbolic PDEs will take well to GPUs.However,we identify a small core of algorithms that take exceptionally well to GPU computing.Based on an analysis of available options,we have been able to identify weighted essentially non-oscillatory(WENO)algorithms for spatial reconstruction along with arbitrary derivative(ADER)algorithms for time extension followed by a corrector step as the winning three-part algorithmic combination.Even when a winning subset of algorithms has been identified,it is not clear that they will port seamlessly to GPUs.The low data throughput between CPU and GPU,as well as the very small cache sizes on modern GPUs,implies that we have to think through all aspects of the task of porting an application to GPUs.For that reason,this paper identifies the techniques and tricks needed for making a successful port of this very useful class of higher order algorithms to GPUs.Application codes face a further challenge—the GPU results need to be practically indistinguishable from the CPU results—in order for the legacy knowledge bases embedded in these applications codes to be preserved during the port of GPUs.This requirement often makes a complete code rewrite impossible.For that reason,it is safest to use an approach based on OpenACC directives,so that most of the code remains intact(as long as it was originally well-written).This paper is intended to be a one-stop shop for anyone seeking to make an OpenACC-based port of a higher order Godunov scheme to GPUs.We focus on three broad and high-impact areas where higher order Godunov schemes are used.The first area is computational fluid dynamics(CFD).The second is computational magnetohydrodynamics(MHD)which has an involution constraint that has to be mimetically preserved.The third is computational electrodynamics(CED)which has involution constraints and also extremely stiff source terms.Together,these three diverse uses of higher order Godunov methodology,cover many of the most important applications areas.In all three cases,we show that the optimal use of algorithms,techniques,and tricks,along with the use of OpenACC,yields superlative speedups on GPUs.As a bonus,we find a most remarkable and desirable result:some higher order schemes,with their larger operations count per zone,show better speedup than lower order schemes on GPUs.In other words,the GPU is an optimal stratagem for overcoming the higher computational complexities of higher order schemes.Several avenues for future improvement have also been identified.A scalability study is presented for a real-world application using GPUs and comparable numbers of high-end multicore CPUs.It is found that GPUs offer a substantial performance benefit over comparable number of CPUs,especially when all the methods designed in this paper are used. 展开更多
关键词 PDEs Numerical schemes-Mimetic High performance computing
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Representing Increasing Virtual Machine Security Strategy in Cloud Computing Computations 认领 引用 被引量：1
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作者 Mohammad Shirzadi 《Electrical Science & Engineering》 2021年第2期7-16,共10页
This paper proposes algorithm for Increasing Virtual Machine Security Strategy in Cloud Computing computations.Imbalance between load and energy has been one of the disadvantages of old methods in providing server and... This paper proposes algorithm for Increasing Virtual Machine Security Strategy in Cloud Computing computations.Imbalance between load and energy has been one of the disadvantages of old methods in providing server and hosting,so that if two virtual severs be active on a host and energy load be more on a host,it would allocated the energy of other hosts(virtual host)to itself to stay steady and this option usually leads to hardware overflow errors and users dissatisfaction.This problem has been removed in methods based on cloud processing but not perfectly,therefore,providing an algorithm not only will implement a suitable security background but also it will suitably divide energy consumption and load balancing among virtual severs.The proposed algorithm is compared with several previously proposed Security Strategy including SC-PSSF,PSSF and DEEAC.Comparisons show that the proposed method offers high performance computing,efficiency and consumes lower energy in the network. 展开更多
关键词 Cloud computing High performance computing Automation Security Server
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