Персона: Ровнягин, Михаил Михайлович
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Институт интеллектуальных кибернетических систем
Цель ИИКС и стратегия развития - это подготовка кадров, способных противостоять современным угрозам и вызовам, обладающих знаниями и компетенциями в области кибернетики, информационной и финансовой безопасности для решения задач разработки базового программного обеспечения, повышения защищенности критически важных информационных систем и противодействия отмыванию денег, полученных преступным путем, и финансированию терроризма.
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Михаил Михайлович
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- ПубликацияТолько метаданныеBurrows - Wheeler Transform in lossless Data compression Problems on hybrid Computing Systems(2020) Rovnyagin, M. M.; Varykhanov, S. S.; Sinelnikov, D. M.; Odintsev, V. V.; Ровнягин, Михаил Михайлович; Синельников, Дмитрий Михайлович© 2020 IEEE.Currently, hybrid computing systems and clusters based on them are used to solve an increasing number of various tasks. This article addresses the issue of lossless data compression on hybrid computing systems. There are sections describing the development and implementation of a stack of lossless data compression algorithms based on the Burrows - Wheeler transform (BWT), as well as a section on data sorting on hybrid computing systems as one of the BWT steps. At the end are the test results of the proposed algorithms.
- ПубликацияТолько метаданныеDistributed Fault-tolerant Platform for Web Applications(2020) Rovnyagin, M. M.; Sinelnikov, D. M.; Odintsev, V. V.; Varykhanov, S. S.; Ровнягин, Михаил Михайлович; Синельников, Дмитрий Михайлович© 2020 IEEE.Web applications are software applications, services or microservices that runs on a remote server. The problem of downtime for web application is important and in some cases, is critical for business. Nowadays, cluster solutions are often used to provide fault-tolerance for applications. But these solutions don't solve the problem of downtime if all instances of application are down. This paper presents a complex approach to provide fault-tolerance for web applications even if all instances of applications in the cluster are down. The approach is based on long-polling and request queueing methods. In this work Apache Kafka and Google Protocol Buffers has been used as the core for the fault-tolerant platform.
- ПубликацияТолько метаданныеMethods for Speeding Up the Retraining of Neural Networks(2022) Varykhanov, S. S.; Sinelnikov, D. M.; Odintsev, V. V.; Rovnyagin, M. M.; Mingazhitdinova, E. F.; Синельников, Дмитрий Михайлович; Ровнягин, Михаил Михайлович© 2022 IEEE.Nowadays, machine learning is widespread and is becoming more complex. Developing and debugging neural networks is becoming more and more time-consuming. Distributed solutions are often used to speed up the learning process. But these solutions do not solve the problem of retraining model from zero if the learning fails. This paper presents a new approach to training models on a large datasets, which can save time and resources during the development. This approach is splitting the model's learning process into separate layers. Each of these layers can be modified and reused for the next layers. The implementation of this approach is based on transfer learning and distributed machine learning techniques. To create reusable network layers, it is proposed to use the methods of automating code parallelization for hybrid computing systems described in the article. These methods include: tracking the readiness and dependencies in the data, speculative execution at the kernel level, creating a DSL
- ПубликацияТолько метаданныеApproach of Program's Concurrency Evaluation in PaaS Cloud Infrastructure(2022) Mingazhitdinova, E. F.; Sinelnikov, D. M.; Odintsev, V. V.; Rovnyagin, M. M.; Varykhanov, S. S.; Синельников, Дмитрий Михайлович; Ровнягин, Михаил Михайлович© 2022 IEEE.In the most cases programs have got different level of concurrency. According to Amdahl's Law, changing the amount of resources may not give a gain in computational efficiency. The article's goal which was determined by the authors is to find out the balance between increasing the amount of resources and improving the efficiency that can be obtained for computation in the K8s cluster. In an effort of resolving the task authors have decided to explore the correlation between increasing the number of podes and time of Spark program processing (data-intensive and compute-intensive computations) in the local minikube for following deployment in K8s.
- ПубликацияТолько метаданныеData Exchange Acceleration Methods in a Decentralized File System(2023) Rovnyagin, M. M.; Sinelnikov, D. M.; Varykhanov, S. S.; Khudoyarova, A. M.; Yakovenko, I. A.; Shirokikh, T. A.; Ровнягин, Михаил Михайлович; Синельников, Дмитрий Михайлович; Яковенко, Иван Алексеевич
- ПубликацияТолько метаданныеIntelligent Docker Container Orchestration for Low Scheduling Latency and Fast Migration in Paas(2023) Rovnyagin, M. M.; Sinelnikov, D. M.; Varykhanov, S. S.; Magazov, T. R.; Kiamov, A. A.; Shirokikh, T. A.; Ровнягин, Михаил Михайлович; Синельников, Дмитрий Михайлович