Partitioning problems in parallel, pipelined and distributed computing

The problem of optimally assigning the modules of a parallel program over the processors of a multiple computer system is addressed. A Sum-Bottleneck path algorithm is developed that permits the efficient solution of many variants of this problem under some constraints on the structure of the partitions. In particular, the following problems are solved optimally for a single-host, multiple satellite system: partitioning multiple chain structured parallel programs, multiple arbitrarily structured serial programs and single tree structured parallel programs. In addition, the problems of partitioning chain structured parallel programs across chain connected systems and across shared memory (or shared bus) systems are also solved under certain constraints. All solutions for parallel programs are equally applicable to pipelined programs. These results extend prior research in this area by explicitly taking concurrency into account and permit the efficient utilization of multiple computer architectures for a wide range of problems of practical interest

Microservices architecture

Сьогоднішні підприємства стикаються з багатьма проблемами які орієнтовані на клієнта в розподільних система. Парадигма мікросервісів стала «наступною великою річчю» для надання ІТ-результатів для підтримки сучасного підприємства, з безліччю постачальників технологій і послуг. Цей документ надає собою набір рекомендацій та кращих практик щодо ефективного використання та управління програмними компонентами підприємства, грунтуючись на кращих концепціях і практиці мікросервісної парадигми розробки програмного забезпечення.Today's Enterprises are facing many challenges in the service oriented, customer experience centric and customer demand driven global environment. Microservice paradigm has emerged as the "next big thing" for delivering IT outcomes to support the modern enterprise, with many technology vendors and. This paper presents a set of recommendations and best practices on the effective use and management of enterprise software components, drawing upon the best of Microservice concepts and practice

Load-Scheduling for Residential Hub Structure for Electricity Distribution

This paper presents models of residential energy hubs which can be readily incorporated into automated decision making technologies in smart grids, and can be solved efficiently in a real-time frame to optimally control all major residential energy loads, storage and production components while properly considering the customer preferences and comfort level. Novel mathematical models for major household demand, i.e., fridge, freezer, dishwasher, washer and dryer, stove, water heater, hot tub, and pool pumps are formulated. Also, mathematical models of other components of a residential energy system including lighting, heating, and air-conditioning are developed, and generic models for solar PV panels and energy storage/generation devices are proposed. The static and dyanamic Programming of minimizing energy consumption, total cost of electricity and gas, emissions, peak load, and/or any combination of these objectives, while considering end-user preferences. Several realistic case studies are carried out to examine the performance of the mathematical model, and experimental tests are carried out to find practical procedures to determine the parameters of the model. The application of the proposed model to a real household in Ontario, Canada is presented for various objective functions

Parallel processing for scientific computations

The main contribution of the effort in the last two years is the introduction of the MOPPS system. After doing extensive literature search, we introduced the system which is described next. MOPPS employs a new solution to the problem of managing programs which solve scientific and engineering applications on a distributed processing environment. Autonomous computers cooperate efficiently in solving large scientific problems with this solution. MOPPS has the advantage of not assuming the presence of any particular network topology or configuration, computer architecture, or operating system. It imposes little overhead on network and processor resources while efficiently managing programs concurrently. The core of MOPPS is an intelligent program manager that builds a knowledge base of the execution performance of the parallel programs it is managing under various conditions. The manager applies this knowledge to improve the performance of future runs. The program manager learns from experience

Efficient algorithms for a class of partitioning problems

The problem of optimally partitioning the modules of chain- or tree-like tasks over chain-structured or host-satellite multiple computer systems is addressed. This important class of problems includes many signal processing and industrial control applications. Prior research has resulted in a succession of faster exact and approximate algorithms for these problems. Polynomial exact and approximate algorithms are described for this class that are better than any of the previously reported algorithms. The approach is based on a preprocessing step that condenses the given chain or tree structured task into a monotonic chain or tree. The partitioning of this monotonic take can then be carried out using fast search techniques

An optimal repartitioning decision policy

A central problem to parallel processing is the determination of an effective partitioning of workload to processors. The effectiveness of any given partition is dependent on the stochastic nature of the workload. The problem of determining when and if the stochastic behavior of the workload has changed enough to warrant the calculation of a new partition is treated. The problem is modeled as a Markov decision process, and an optimal decision policy is derived. Quantification of this policy is usually intractable. A heuristic policy which performs nearly optimally is investigated empirically. The results suggest that the detection of change is the predominant issue in this problem

Алгоритми балансування навантаження в Грід-системах

Проведено аналіз стратегій балансування навантаження в Грід-системах та порівняльний аналіз наявних алгоритмів розподілу потоку завдань між обчислювальними ресурсами Грід-середовища.Проведен анализ стратегий балансирования нагрузки в Грид-системах и сравнительный анализ имеющихся алгоритмов распределения потока заданий между вычислительными ресурсами Грид-среды.The analysis of strategies of balancing load in the Grid-systems and comparative analysis of existing algorithms of the distribution of flow of the tasks between computing resources of a Grid environment are shown

Approximate algorithms for partitioning and assignment problems

The problem of optimally assigning the modules of a parallel/pipelined program over the processors of a multiple computer system under certain restrictions on the interconnection structure of the program as well as the multiple computer system was considered. For a variety of such programs it is possible to find linear time if a partition of the program exists in which the load on any processor is within a certain bound. This method, when combined with a binary search over a finite range, provides an approximate solution to the partitioning problem. The specific problems considered were: a chain structured parallel program over a chain-like computer system, multiple chain-like programs over a host-satellite system, and a tree structured parallel program over a host-satellite system. For a problem with m modules and n processors, the complexity of the algorithm is no worse than O(mnlog(W sub T/epsilon)), where W sub T is the cost of assigning all modules to one processor and epsilon the desired accuracy

Алгоритмы балансирования нагрузки в Грид-системах

Проведено аналіз стратегій балансування навантаження в Грід-системах та порівняльний аналіз наявних алгоритмів розподілу потоку завдань між обчислювальними ресурсами Грід-середовища.The analysis of strategies of balancing load in the Grid-systems and comparative analysis of existing algorithms of the distribution of flow of the tasks between computing resources of a Grid environment are shown.Проведен анализ стратегий балансирования нагрузки в Грид-системах и сравнительный анализ имеющихся алгоритмов распределения потока заданий между вычислительными ресурсами Грид-среды

Task allocation in distributed multimedia systems based on the host-satellite model

Multimedia applications require intermediate processing between media sources and sinks. In addition to end-user machines intermediate computers can be used for performing media processing. This possibility leads to the problem of allocating processing components on various computers. In this paper, we study this problem in the context of star-shaped application graphs which have to be allocated between given end-user machines (satellites) and a central computer (host). The problem is formulated in terms of best achievable bottleneck resource usage. Several approaches are considered including anapproximate scheme and two fast-heuristics. Performance measurements show the efficiency of the considered approaches. A discussion of our approach shows important differences to solutions provided for related problems of graph partitioning and mapping