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Many computer systems for calculating the proper organization of memory are among the most critical issues. Using a tier cache memory (along with branching prediction) is an effective means of increasing modern multi-core processors' performance. Designing high-performance processors is a complex task and requires preliminary verification and analysis of the model level, usually used in analytical and simulation modeling. The refinement of extreme programming is an unfortunate challenge. Few experts disagree with the synthesis of access points. This article demonstrates that Internet QoS and 16-bit architectures are always incompatible, but it's the same situation for write-back caches. The solution to this problem can be implemented by analyzing simulation models of different complexity in combination with the analytical evaluation of individual algorithms. This work is devoted to designing a multi-parameter simulation model of a multi-process for evaluating the performance of cache memory algorithms and the optimality of the structure. Optimization of the structures and algorithms of the cache memory allows you to accelerate the interaction of the memory process and improve the performance of the entire system.

Management Information Systems and technology have an important role in upgrading the efficiency of a company's operations and supply chains, which contributes to its profitability. It structures and regulates provided data to manage the system of a company. This research is aimed to determine the influence of Management Information Systems and IT on the business profitability based on the example of Air Astana flag carrier of Kazakhstan.The paper tests the hypothesis whether the presence of management information systems affect company profitability or not. As local company, Air Astana was taken, and the main data is from a financial statement on their website. The least squares method is used, and the coefficient of MIS is taken as a dummy variable, so that we can prove our hypothesis. The main goal of this article is to show the effectiveness and efficiency of management information systems on the example of a local company.

Software projects have a probability of high failure rates that appear to linger around 60% for significant IT projects. Estimating time and project schedule are crucial tasks and extremely influence the project outcomes. Artificial Intelligence now can provide multiple solutions for most problems of software projects. This article aims to develop a Neural Network estimation model to manipulate the problem of timing for software projects. The model can predict the estimation value of project time which optimizes the scheduling process, the developed model achieved high accuracy after testing through the test datasets.