Book chapter
Алгоритм деления по вычислительным мощностям для распределенного МД-моделирования
In book
A new computer architecture named object-attribute is offered in the article. Computer of the architecture have all necessary properties for Artificial Intelligence: abstraction of data and program, height concurrency, isomorphism of data and program (i.e. possibility of painless changing of program and data structures), training and self-training of computer system, dataflow, integration of data and program, generation of object description from simple description to complex description, implementation of distribute computer system.
The small number of dust particles in the system and their large kinetic energy make it impossible to use the notion of “temperature” to describe the dynamics of dust particles in gas discharge without substantiation. We simulated the isolated and open systems of dust particles based on the molecular dynamics method and suggested the substantiation of applying the term “temperature” to describe the dynamics of the system of dust particles in the gas discharge plasma. The closeness of the equilibrium velocity distribution for a small number of particles and the Maxwell distribution for isolated and open systems is shown. It is found that the average kinetic energy precisely coincides with the velocity distribution parame ter of the dust particles. The necessity of separation the temperature of the horizontal motion and the temperature of the vertical motion of dust particles is shown.
This chapter describes an economic model for independent job flow management in distributed computing environments with non-dedicated resources. The model is based on the concept of fair resource distribution between users and owners of computational nodes by means of economic mechanisms in a virtual organization. Scheduling is performed in cycles in accordance with dynamically updated schedules on local processor nodes. Schedule optimization is performed using dynamic programming methods using the set of criteria in accordance with the economic policy of the virtual organization.
This chapter describes an economic model for independent job flow management in distributed computing environments with non-dedicated resources. The model is based on the concept of fair resource distribution between users and owners of computational nodes by means of economic mechanisms in a virtual organization. Scheduling is performed in cycles in accordance with dynamically updated schedules on local processor nodes. Schedule optimization is performed using dynamic programming methods using the set of criteria in accordance with the economic policy of the virtual organization.
This work presents slot selection algorithms in economic models for independent job batch scheduling in distributed computing with non-dedicated resources. Existing approaches towards resource co-allocation and multiprocessor job scheduling in economic models of distributed computing are based on search of time-slots in resource occupancy schedules. The sought time-slots must match requirements of necessary span, computational resource properties, and cost. Usually such scheduling methods consider only suited variant of time-slot set. This work discloses a scheduling scheme that features multi-variant search. Two algorithms of linear complexity for search of alternative variants are proposed and compared. Having several optional resource configurations for each job makes an opportunity to perform an optimization of execution of the whole batch of jobs and to increase overall efficiency of scheduling.
In this work, we present slot selection algorithms for job batch scheduling in distributed computing with non-dedicated resources. Jobs are parallel applications and these applications are independent. Existing approaches towards resource co-allocation and parallel job scheduling in economic models of distributed computing are based on search of time-slots in resource occupancy schedules. The sought time-slots must match requirements of necessary span, computational resource properties, and cost. Usually such scheduling methods consider only one suited variant of time-slot set. This work discloses a scheduling scheme that features multi-variant search. Two algorithms of linear complexity for search of alternative variants are proposed. Having several optional resource configurations for each job makes an opportunity to perform an optimization of execution of the whole batch of jobs and to increase overall efficiency of scheduling.