The article discusses the features of modern processor’s microarchitecture, the method of instruction’s and micro-operation’s accelerated execution. The research focuses on the organization of the decoding stage in the CPU core pipeline and Macro- and Micro-fusion algorithms. The Macro- and Micro-fusion mechanisms are defined. A computer simulator has been developed to explore these mechanisms. The developed software has a user-friendly interface, is easy to use, and combines training and research options. The computer simulator demonstrates the sequence of mechanism’ s implementation; the resulting macro-or microoperations set after Macro- and Micro-fusion, and also reflects each algorithm features for different processor’s families. The software allows you to use either a pre-prepared file with Assembler (x86) code fragments as source data, or enter/change the source code fragments at your request. The main combinations of machine instructions that can be fused into a single macro-operation are considered, as well as instructions that can be decoded into fused micro-operations. The simulator can be useful both for in Computer Science & Engineering students, especially for on-line education and for researchers and General-purpose CPU cores developers.
Modern educational process involves the use of electronic educational environments. These are special information systems that are both a means for storing educational materials and a tool for conducting tests, collecting homework, keeping a grade book, and working together. Such environments produce a large amount of data containing the recorded behavior of students and teachers within the educational process. This paper proposes an approach that allows one to analyze such data and discover typical student trajectories that lead to successful or unsuccessful learning outcomes. It is shown how process mining can be used to build models of the educational process based on the available data. We also show how you can evaluate the extent to which the synthesized model reflects the actual behavior of the system recorded in event logs. The paper contains not only a description of the proposed approach, but also a case study with its application to a real data set for an undergraduate educational program. It is clearly shown how, using our approach, it is possible to find out what factors lead to the formation of successful and unsuccessful student trajectories. The bottlenecks of the educational process were identified, as well as errors in the data, indicating the incorrect operation of the system. As a result of the analysis, points of special attention for administrators of the educational program were identified, as well as some signal events, the appearance of which in a student’s individual trajectory can be an alarm. The application of the approach involves the use of free open source software, which further facilitates its deployment in a variety of educational organizations.
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