Исследование эффективности программной реализации многопотокового алгоритма масштабирования методом билинейной интерполяции
The article compares efficiency of sequential and parallel approaches to digital image zooming in software implementation. The method of bilinear interpolation is chosen as a sample. For the study purposes, a test routine was written in С# language. In the tests the operate time of sequential and parallel processing of the same images was compared. To have broader picture, images of various resolution (size) were tested. The article presents plots to describe dynamics of time consumption by accomplished zooming operations in the sequential and parallel approaches versus the original image resolution. The test routine results have confirmed potential speedup of the operation in case of multisequencing. The speedup limitations of multistream implementation of the zooming algorithm have been defined. The article gives suggestions on candidate memory formation for the parallel processing and induces on the best suited operation of the memory, which is the shared memory chart. The presented studies serve as the basis for development of an effective algorithm for large-scale parallelism and parallel-stream pipeline processing in the module of zooming for hardware–software implementation.
Key words: zooming, parallel processing, bilinear interpolation.
In big data problems the data usually are collected on many sites, have a huge volume, and new pieces of data are constantly generated. It is often impossible to collect all the data needed for a research project on one computer, and even impractical, since one computer would not be able to process it in a reasonable time. An appropriate data analysis algorithm should, working in parallel on many computers, extract from each set of raw data some intermediate compact “information”, gradually combine and update it, and finally, use the accumulated information to produce the result. When new data appears, it must extract information from them, add it to the accumulated one, and eventually update the result. We consider several examples of a suitable transformation of processing algorithms, discuss specific features of the emerging information spaces and, in particular, their algebraic properties. We also show that the information space often can be equipped with an order relation that reflects the "quality" of the information.
In their recent paper, Marchant, Simons, and De Fockert (2013) claimed that the ability to average between multiple items of different sizes is limited by small samples of arbitrarily attended members of a set. This claim is based on a finding that observers are good at representing the average when an ensemble includes only two sizes distributed among all items (regular sets), but their performance gets worse when the number of sizes increases with the number of items (irregular sets). We argue that an important factor not considered by Marchant et al. (2013) is the range of size variation that was much bigger in their irregular sets. We manipulated this factor across our experiments and found almost the same efficiency of averaging for both regular and irregular sets when the range was stabilized. Moreover, highly regular sets consisting only of small and large items (two-peaks distributions) were averaged with greater error than sets with small, large, and intermediate items, suggesting a segmentation threshold determining whether all variable items are perceived as a single ensemble or distinct subsets. Our results demonstrate that averaging can actually be parallel but the visual system has some difficulties with it when some items differ too much from others.
The need to transform existing algorithms in Big Data Systems is considered. The transformation must allow independent and parallel processing of separate fragments of data. The characteristic aspects of a well-organized intermediate compact form of information and its natural algebraic properties are studied and an illustrative example is provided.
The Data in “big data” sets, as a rule, have a huge volume, are distributed among numerous sites and are constantly replenished. As a result even a simplest analysis of big data faces serious difficulties. To apply traditional processing all the relevant data has to be collected in one place and arranged in the form of convenient structures. Only then the corresponding algorithm processes these structures and produces the result of analysis. In the case of big data, it can be just impossible to collect all the relevant data on one computer, and even impractical, since one computer would not be able to process them in a reasonable time. An appropriate data analysis algorithm should, working in parallel on many computers, extract from each set of raw data some intermediate compact “information”, gradually combine and update it, and finally, use the accumulated information to produce the result. Upon arrival of new pieces of data, it should be able to add them to the accumulated information and eventually renew the result. We will discuss specific features of such well-arranged intermediate form of information, reveal its natural algebraic properties, and present several examples. We will also see that in many important data processing problems the appropriate information space may become equipped with an ordering which reflects the “quality” of the information. It turns out that such an intermediate form of information representation in some sense reflects the very essence of the information contained in the data. This leads us to a completely new, ‘practical’ approach to the notion of information.
The paper describes categories of costs which can be included in total cost of ownership (TCO) of information-analytical system and which are connected with the data integration system (DIS). Some problems of creating DIS are described. The streaming architecture of DIS, which helps to solve problems of stability and scalability of DIS and to lower TCO of IAS is proposed.
The papers in this book comprise the proceedings of the 46th International Conference on Parallel Processing Workshops — ICPPW 2017 — 14 August 2017 Bristol, United Kingdom.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.
Let G be a semisimple algebraic group whose decomposition into the product of simple components does not contain simple groups of type A, and P⊆G be a parabolic subgroup. Extending the results of Popov , we enumerate all triples (G, P, n) such that (a) there exists an open G-orbit on the multiple flag variety G/P × G/P × . . . × G/P (n factors), (b) the number of G-orbits on the multiple flag variety is finite.
I give the explicit formula for the (set-theoretical) system of Resultants of m+1 homogeneous polynomials in n+1 variables