Many Task Computing(MTC)is a new class of computing paradigm in which the aggregate number of tasks,quantity of computing,and volumes of data may be extremely large.With the advent of Cloud computing and big data era,...Many Task Computing(MTC)is a new class of computing paradigm in which the aggregate number of tasks,quantity of computing,and volumes of data may be extremely large.With the advent of Cloud computing and big data era,scheduling and executing large-scale computing tasks efficiently and allocating resources to tasks reasonably are becoming a quite challenging problem.To improve both task execution and resource utilization efficiency,we present a task scheduling algorithm with resource attribute selection,which can select the optimal node to execute a task according to its resource requirements and the fitness between the resource node and the task.Experiment results show that there is significant improvement in execution throughput and resource utilization compared with the other three algorithms and four scheduling frameworks.In the scheduling algorithm comparison,the throughput is 77%higher than Min-Min algorithm and the resource utilization can reach 91%.In the scheduling framework comparison,the throughput(with work-stealing)is at least 30%higher than the other frameworks and the resource utilization reaches 94%.The scheduling algorithm can make a good model for practical MTC applications.展开更多
The activation of multisite high-entropy alloy(HEA)electrocatalysts is helpful for improving the atomic utilization of each metal in water electrolysis catalysis.Herein,well-dispersed HEA nanocrystals on Nrich graphen...The activation of multisite high-entropy alloy(HEA)electrocatalysts is helpful for improving the atomic utilization of each metal in water electrolysis catalysis.Herein,well-dispersed HEA nanocrystals on Nrich graphene with abundant M–pyridinic N–C bonds were synthesized through an ultrasonic-assisted confinement synthesis method.Operando Raman analysis and density functional theory calculations revealed that the electrocatalysts presented the optimal electronic rearrangement with fast ratedetermined H_(2)O dissociation kinetics and favorable H^(*)adsorption behavior that greatly enhanced hydrogen generation in alkaline electrolyte.A small overpotential of only 138.6 mV was required to obtain the current density of 100 mA cm^(-2) and the Tafel slope of as low as 33.0 mV dec^(-1),which was considerably smaller than the overpotentials of the counterpart with poor M–pyridinic N–C bonds(290.4 mV)and commercial Pt/C electrocatalysts(168.6 mV).The atomic structure,coordination environment,and electronic structure were clarified.This work provides a new avenue toward activating HEA as advanced electrocatalysts and promotes the research on HEA for energy-related electrolysis.展开更多
基金ACKNOWLEDGEMENTS The authors would like to thank the reviewers for their detailed reviews and constructive comments, which have helped improve the quality of this paper. The research has been partly supported by National Natural Science Foundation of China No. 61272528 and No. 61034005, and the Central University Fund （ID-ZYGX2013J073）.
文摘Many Task Computing(MTC)is a new class of computing paradigm in which the aggregate number of tasks,quantity of computing,and volumes of data may be extremely large.With the advent of Cloud computing and big data era,scheduling and executing large-scale computing tasks efficiently and allocating resources to tasks reasonably are becoming a quite challenging problem.To improve both task execution and resource utilization efficiency,we present a task scheduling algorithm with resource attribute selection,which can select the optimal node to execute a task according to its resource requirements and the fitness between the resource node and the task.Experiment results show that there is significant improvement in execution throughput and resource utilization compared with the other three algorithms and four scheduling frameworks.In the scheduling algorithm comparison,the throughput is 77%higher than Min-Min algorithm and the resource utilization can reach 91%.In the scheduling framework comparison,the throughput(with work-stealing)is at least 30%higher than the other frameworks and the resource utilization reaches 94%.The scheduling algorithm can make a good model for practical MTC applications.
基金supported by the National Natural Science Foundation of China(21838003,51621002)the Innovation Program of Shanghai Municipal Education Commissionthe Fundamental Research Funds for the Central Universities。
文摘The activation of multisite high-entropy alloy(HEA)electrocatalysts is helpful for improving the atomic utilization of each metal in water electrolysis catalysis.Herein,well-dispersed HEA nanocrystals on Nrich graphene with abundant M–pyridinic N–C bonds were synthesized through an ultrasonic-assisted confinement synthesis method.Operando Raman analysis and density functional theory calculations revealed that the electrocatalysts presented the optimal electronic rearrangement with fast ratedetermined H_(2)O dissociation kinetics and favorable H^(*)adsorption behavior that greatly enhanced hydrogen generation in alkaline electrolyte.A small overpotential of only 138.6 mV was required to obtain the current density of 100 mA cm^(-2) and the Tafel slope of as low as 33.0 mV dec^(-1),which was considerably smaller than the overpotentials of the counterpart with poor M–pyridinic N–C bonds(290.4 mV)and commercial Pt/C electrocatalysts(168.6 mV).The atomic structure,coordination environment,and electronic structure were clarified.This work provides a new avenue toward activating HEA as advanced electrocatalysts and promotes the research on HEA for energy-related electrolysis.
