For the past several decades, parallel processing has become an important research subject in the computer science area. According to the statistics, in executing a numerical program, most of time is spent on the loops. If we can use the technique of loop restructuring in the parallelizing compiler such that the conventional sequential program can be executed by exploiting the characteristics of vector machine or parallel machine, the execution efficiency will be greatly improved. In the parallelizing compiler, data dependence analysis is very important because it provides the information for loop restructuring. Data dependence analysis is necessary in order to determine whether a loop can be vectorized or parallelized. It analyzes whether the same array element or variable will be accessed more than once in a loop (e.g. access the same memory location more than once in loop execution). In the recent years, the researches on parallelizing compiler are considerable. But, data dependence analysis is still a bottleneck. There are many data dependence test such as Banerjee Test, test, Omega Test, I Test, Power Test, ... and so on, which have been used in the design of parallelizing compiler. In the thesis, we will propose a novel exact data dependence test method called Interval Reduced test (IR test). This method reduces the integer boundary of each constraint variable by repeatedly projection. When the effective region of a variable is reduced to be empty, the constraint containing this variable has no integer solution and the memory accesses under this constraint are therefore independent. The IR test is only suitable for the loops in which the loop bounds are rectangular, triangular, or unknown at compiling-time in some limited condition. To enhance the data dependence analysis capability of the IR test, we proposed the Extension-IR test in this thesis to extend the dependence testing range of one-dimensional array references to linear subscripts with variable bounds under any given direction vector. The Extension-IR test can solve in effective polynomial time. When array subscripts are non-linear expressions or too complex to analyze by the existing data dependence testing schemes, we devise a new parallelization algorithm called non-linear array subscripts test (NLA test) to deal with. The iterations subject to loop-carried dependence are scheduled into different wavefronts, while the iterations with no loop-carried dependence are assigned into the same wavefront. Based on the wavefront information, the original loop is transformed into parallel code for execution at run-time. Loop interchange is an important restructuring technique for supporting vectorization and parallelization. In this thesis, we proposed a technique, which can determine efficiently, whether loops can be interchanged between two non-adjacent loops on perfect nested loop or some imperfectly nested loop. A method for determining whether two arbitrary levels in perfectly nested loops, which contain IF and GOTO statements, can be interchanged is also presented in this thesis.

The thesis analyzes the relationship of the perceived happiness level and the level of work busyness of full time employees. For this purpose, a questionnaire was built which mapped happiness and busyness with considering both subjective and objective variables. 205 employees participated in the questionnaire survey. The sample showed above-average education, a high level of busyness and above-average salary (or wages). It has been shown that the work happiness level depends on the level of workload: the unbusy employees are the least happy ones. Influence of ambitions or influence of the importance of work area to the relationship of happiness level and workload level has not been confirmed.

The goal of this diploma thesis is to study and implement selected methods of static code analysis for C# programs translated into the Common Intermediate Language. The results of this work are integrated into the ParallaX Development Environment system. This diploma thesis focuses on Structural, Points-to and Dependence. analysis. Powered by TCPDF (www.tcpdf.org)

The main aim of this thesis is describe and evaluate the price trend of beef in selected countries of European Union during the years 2003 - 2013. In the first part of this thesis you can find theoretical knowledge from the sphere of price or agrarian market. The practical part describes the development of price of beef in selected countries using various statistical indicators and mathematical-economic methods. The conclusion contains a description of the current situation of beef on the world market including its prediction on the basis of international institutions such as the OECD, FAO and FAPRI.

Les microprocesseurs et les architectures parallèles d'aujourd'hui lancent de nouveaux défis aux techniques de compilation. En présence de parallélisme, les optimisations deviennent trop spécifiques et complexes pour être laissées au soin du programmeur. Les techniques de parallélisation automatique dépassent le cadre traditionnel des applications numériques et abordent de nouveaux modèles de programmes, tels que les nids de boucles non affines, les appels récursifs et les structures de données dynamiques. Des analyses précises sont au c{\oe}ur de la détection du parallélisme, elles rassemblent des informations à la compilation sur les propriétés des programmes à l'exécution. Ces informations valident des transformations utiles pour l'extraction du parallélisme et la génération de code parallèle. Cette thèse aborde principalement des analyses et des transformations avec une vision par instances, c'est-à-dire considérant les propriétés individuelles de chaque instance d'une instruction à l'exécution. Une nouvelle formalisation à l'aide de langages formels nous permet tout d'abord d'étudier une analyse de dépendances et de définitions visibles par instances pour programmes récursifs. L'application de cette analyse à l'expansion et la parallélisation de programmes récursifs dévoile des résultats encourageants. Les nids de boucles quelconques font l'objet de la deuxième partie de ce travail. Une nouvelle étude des techniques de parallélisation fondées sur l'expansion nous permet de proposer des solutions à des problèmes d'optimisation cruciaux.

To parallelize a sequential source code, a parallelization strategy must be defined that transforms the sequential source code into an equivalent parallel version. Since parallelizing compilers can sometimes transform sequential loops and other well-structured codes into parallel ones automatically, we are interested in finding a solution to parallelize semi-automatically codes that compilers are not able to parallelize automatically, mostly because of weakness of classical data and control dependence analysis, in order to simplify the process of transforming the codes for programmers.Invasive Interactive Parallelization (IIP) hypothesizes that by using anintelligent system that guides the user through an interactive process one can boost parallelization in the above direction. The intelligent system's guidance relies on a classical code analysis and pre-defined parallelizing transformation sequences. To support its main hypothesis, IIP suggests to encode parallelizing transformation sequences in terms of IIP parallelization strategies that dictate default ways to parallelize various code patterns by using facts which have been obtained both from classical source code analysis and directly from the user.In this project, we investigate how automated reasoning can supportthe IIP method in order to parallelize a sequential code with an acceptable performance but faster than manual parallelization. We have looked at two special problem areas: Divide and conquer algorithms and loops in the source codes. Our focus is on parallelizing four sequential legacy C programs such as: Quick sort, Merge sort, Jacobi method and Matrix multipliation and summation for both OpenMP and MPI environment by developing an interactive parallelizing assistance tool that provides users with the assistanceneeded for parallelizing a sequential source code.