Software Design Based on Using Ontologies and Algorithm Algebra

This chapter proposes an approach to the automated development of programs based on the use of ontological facilities and algebra-algorithmic toolkit for design and synthesis of programs (IDS). The program design ontology, developed using Protégé system and represented in OWL format, includes concepts from various subject domains (sorting, meteorological forecasting, and other) intended for description of main program objects: data, functions, and relations between them. IDS toolkit generates the initial (skeleton) algorithm scheme based on its ontological description extracted from OWL file. The generated scheme is the basis of further design of the algorithm and synthesis of a program in a target programming language. The approach is illustrated by examples of developing parallel sorting, meteorological forecasting, and N-body simulation programs.

Executing Collaborative Brainstorming Idea Organization Through Distributed and Parallel Sorting

This chapter examines the post-convergence process of organizing ideas that are generated during collaborative idea generation activities. The method presented reduces the impact of organizing brainstorming ideas on individual participants by dividing the organization activity into smaller, discrete tasks that can be completed individually, and in parallel, by the participants. The entire pool of brainstorming ideas is subdivided into smaller pools and each participant is then tasked with organizing one of the subsets of ideas. The results show that by dividing up the overall activity into subtasks, the subjects experienced a more favorable environment. Furthermore, the subjects were able to work through their subset of ideas and produce results that were similar to those performing the full sort of the entire pool.

DIAGONAL COMMUTATION MODEL FOR PARALLEL SORTING OF DATA ARRAYS

Oбъект исследования - алгоритмы параллельной сортировки с применением базовой операции «сравнение-обмен». Цель исследования - сокращение шагов работы алгоритма сортировки массива данных за счет уменьшения количества промежуточных перестановок элементов массива. Цель достигается разработкой оригинальной схемы коммутаций элементов массива. Данная схема составляет основу модели диагональных коммутаций пар элементов массива. Массив имеет 2d-представление, что позволяет объединить в пары элементы из его различных половин. За счет 2d-представления массива образуемые пары элементов позволяют уменьшить количество перестановок. Новизна модели диагональных коммутаций состоит в том, что операции «сравнение-обмен» параллельно выполняются на неконфликтующих парах элементов, взятых из различных половин массива. Это свойство модели позволяет «прыжками» перемещать элемент в необходимую позицию массива. Модель диагональных коммутаций объединена с известной моделью четно-нечетной сортировки. В результате объединения был получен алгоритм параллельной сортировки с гибридной схемой коммутации. Эта схема реализует на четных шагах предложенную модель, а на нечетных шагах - модель четно-нечетной сортировки. Моделирование алгоритмов четно-нечетной сортировки и гибридной сортировок показало преимущество разработанной модели. Расширение четно-нечетной сортировки моделью диагональных коммутаций позволяет сократить среднее число шагов сортировки. Кроме четно-нечетной сортировки, модель диагональных коммутаций применима для алгоритмов параллельной сортировки, использующих базовую операцию «сравнение-обмен» - сортировки Батчера, Шелла, слиянием The object of the research is parallel sorting algorithms using the basic operation "compare-swap". The aim of the research is to reduce the steps of the algorithm for sorting the data array by reducing the number of intermediate permutations of the array elements. The goal is achieved by developing an original switching circuit of the array elements. This circuit forms the basis of the model for diagonal commutation of pairs of array elements. The array is 2D, which allows one to pair elements from its different halves. Due to the 2D representation of the array, the formed pairs of elements allow reducing the number of permutations. The novelty of the diagonal commutation model is that the “compare-exchange” operations are performed in parallel on non-conflicting pairs of elements taken from different halves of the array. This property of the model allows one to "jump" the element to the desired position in the array. The diagonal commutation model is combined with the well-known odd-even sorting model. The combination resulted in a parallel sorting algorithm with a hybrid switching scheme. This scheme implements the proposed model at even steps, and the even-odd sorting model at odd steps. Modeling algorithms for odd-even sorting and hybrid sorting showed the advantage of the developed model. Extension of even-odd sorting by the diagonal commutation model allows to reduce the average number of sorting steps by 6-10%. In addition to odd-even sorting, the diagonal commutation model is applicable for parallel sorting algorithms using the basic comparison-exchange operation - Butcher, Shell, merge sorting

Analisis Kinerja Algoritma Quick Double Merge Sort Paralel Menggunakan openMP

Processor technology currently tends to increase the number of cores more than increasing the clock speed. This development is very useful and becomes an opportunity to improve the performance of sequential algorithms that are only done by one core. This paper discusses the sorting algorithm that is executed in parallel by several logical CPUs or cores using the openMP library. This algorithm is named QDM Sort which is a combination of sequential quick sort algorithm and double merge algorithm. This study uses a data parallelism approach to design parallel algorithms from sequential algorithms. The data used in this study are the data that have not been sorted and also the data that has been sorted is integer type which is stored in advance in a file. The parameter measured to determine the performance of the QDM Sort algorithm is speedup. In a condition where a large amount of data is above 4096 and the number of threads in QDM Sort is the same as the number of logical CPUs, the QDM Sort algorithm has a better speedup compared to the other parallel sorting algorithms discussed in this study. For small amounts of data it is still better to use sequential sorting algorithm.