Parallel Data Testing Algorithm in the "algo.ubtuit.uz" System
Parallel computing is a fundamental technique in modern software development, enabling the efficient execution of large-scale computations by distributing workloads across multiple processing units. This paper presents a detailed analysis of a parallel data processing platform, algo.ubtuit.uz, which...
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| Vydáno v: | 2025 IEEE 26th International Conference of Young Professionals in Electron Devices and Materials (EDM) s. 2140 - 2144 |
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| Jazyk: | angličtina |
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IEEE
27.06.2025
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| ISSN: | 2325-419X |
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| Abstract | Parallel computing is a fundamental technique in modern software development, enabling the efficient execution of large-scale computations by distributing workloads across multiple processing units. This paper presents a detailed analysis of a parallel data processing platform, algo.ubtuit.uz, which is designed to enhance programming education and competition preparation. The platform integrates parallel computing techniques to optimize the execution of user-submitted programming solutions, thereby reducing latency and improving system throughput. By utilizing task and data parallelism, the system is capable of executing multiple test cases simultaneously, significantly reducing execution time compared to traditional sequential approaches. Furthermore, we evaluate the impact of parallel execution on resource utilization and scalability. Experimental results demonstrate that the parallelized testing process improves response time by up to 60%, allowing for more efficient handling of high user loads during peak competition periods. The comparison between sequential and parallel execution highlights the advantages of leveraging parallel computing techniques in online judge systems. The study also discusses the integration of cloud-based parallel processing solutions to further enhance computational performance. The findings of this research provide insights into the design and implementation of high-performance computing platforms tailored for algorithmic problem-solving. |
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| AbstractList | Parallel computing is a fundamental technique in modern software development, enabling the efficient execution of large-scale computations by distributing workloads across multiple processing units. This paper presents a detailed analysis of a parallel data processing platform, algo.ubtuit.uz, which is designed to enhance programming education and competition preparation. The platform integrates parallel computing techniques to optimize the execution of user-submitted programming solutions, thereby reducing latency and improving system throughput. By utilizing task and data parallelism, the system is capable of executing multiple test cases simultaneously, significantly reducing execution time compared to traditional sequential approaches. Furthermore, we evaluate the impact of parallel execution on resource utilization and scalability. Experimental results demonstrate that the parallelized testing process improves response time by up to 60%, allowing for more efficient handling of high user loads during peak competition periods. The comparison between sequential and parallel execution highlights the advantages of leveraging parallel computing techniques in online judge systems. The study also discusses the integration of cloud-based parallel processing solutions to further enhance computational performance. The findings of this research provide insights into the design and implementation of high-performance computing platforms tailored for algorithmic problem-solving. |
| Author | Bekjanov, Ruzimboy Rajabov, Sherzod Rakhmonova, Nilufar Yusupova, Janar Bahrom, Reyimberganov Matyakubov, Marks |
| Author_xml | – sequence: 1 givenname: Janar surname: Yusupova fullname: Yusupova, Janar email: yusupovajanar1992@gmail.com organization: Urgench Branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi,Department of Software Engineering,Urgench,Uzbekistan – sequence: 2 givenname: Marks surname: Matyakubov fullname: Matyakubov, Marks email: marks2902226@mail.ru organization: Tashkent University of Information Technologies named after Muhammad al-Khwarizmi,Department of Algorithms and mathematical modeling,Tashkent,Uzbekistan – sequence: 3 givenname: Nilufar surname: Rakhmonova fullname: Rakhmonova, Nilufar email: n.raxmonova@tuit.uz organization: Tashkent University of Information Technologies named after Muhammad al-Khwarizmi,Department of Algorithms and mathematical modeling,Tashkent,Uzbekistan – sequence: 4 givenname: Ruzimboy surname: Bekjanov fullname: Bekjanov, Ruzimboy email: ruzimboybekjanov@gmail.com organization: Urgench Branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi,Urgench,Uzbekistan – sequence: 5 givenname: Sherzod surname: Rajabov fullname: Rajabov, Sherzod email: sherzodradjabov0625@gmail.com organization: Urgench Branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi,Urgench,Uzbekistan – sequence: 6 givenname: Reyimberganov surname: Bahrom fullname: Bahrom, Reyimberganov email: bahromreyimberganov0311@gmail.com organization: Urgench Branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi,Urgench,Uzbekistan |
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| SubjectTerms | algo.ubtuit.uz Computational efficiency high-performance computing online judge systems Parallel computing Parallel processing Problem-solving programming education Programming profession Resource management Scalability Software algorithms Testing Throughput Time factors |
| Title | Parallel Data Testing Algorithm in the "algo.ubtuit.uz" System |
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