High-Performance Computing for Efficient Transaction Processing: A Comparative Study of Parallel and Sequential Execution using SQLite

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Detaylı Bibliyografya
Yayımlandı:The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings (2024)
Yazar: CVRoshan Balaji
Diğer Yazarlar: Shaman, K R, VPritham Raj, Kumar, NNithish, Kumaran, K
Baskı/Yayın Bilgisi:
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Online Erişim:Citation/Abstract
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024 7 |a 10.1109/ICICNIS64247.2024.10823214  |2 doi 
035 |a 3153911969 
045 2 |b d20240101  |b d20241231 
084 |a 228229  |2 nlm 
100 1 |a CVRoshan Balaji  |u School of Computer Science and Engineering, Vellore Institute of Technology,Chennai campus,India 
245 1 |a High-Performance Computing for Efficient Transaction Processing: A Comparative Study of Parallel and Sequential Execution using SQLite 
260 |b The Institute of Electrical and Electronics Engineers, Inc. (IEEE)  |c 2024 
513 |a Conference Proceedings 
520 3 |a Conference Title: 2024 International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS)Conference Start Date: 2024, Dec. 17 Conference End Date: 2024, Dec. 18 Conference Location: Bengaluru, IndiaHigh-performance computing (HPC) has become an essential tool for improving the efficiency and scalability of transaction processing systems, especially as data volumes continue to grow in fields like finance, e-commerce, and blockchain. This paper presents a comparative study of parallel and sequential transaction processing methods using an SQLite database. Specifically, the research investigates the impact of HPC techniques on transaction throughput, processing speed, and efficiency by simulating 1,000 user transactions. The study employs Python's multiprocessing module to simulate parallel execution, contrasting it with traditional sequential execution. Key performance indicators, including execution time, transaction success rate, and system efficiency, were analyzed to determine the advantages of parallel processing in a transaction-heavy environment. Our results reveal that parallel execution significantly reduces processing time, boosts throughput, and increases overall system efficiency compared to sequential processing. Additionally, the study discusses how parallel processing techniques can address common bottlenecks in transaction-heavy applications and provide solutions for improving the performance of large-scale, data-intensive systems. The findings demonstrate the potential for using HPC to optimize database operations, particularly in systems where high-volume transaction processing is a critical requirement. Future work will explore advanced parallelization strategies, fault tolerance mechanisms, and integrations with distributed databases and blockchain systems. This research contributes to the growing body of knowledge on optimizing transaction processing in high-performance computing environments, with potential applications across various sectors, including financial services, e-commerce, and blockchain technology. 
653 |a Parallel processing 
653 |a Comparative studies 
653 |a Computation 
653 |a Finance 
653 |a Databases 
653 |a Fault tolerance 
653 |a Efficiency 
653 |a Optimization 
653 |a Blockchain 
653 |a Electronic commerce 
653 |a Transaction processing 
653 |a Multiprocessing 
653 |a High performance computing 
653 |a Software 
653 |a Economic 
700 1 |a Shaman, K R  |u School of Computer Science and Engineering, Vellore Institute of Technology,Chennai campus,India 
700 1 |a VPritham Raj  |u School of Computer Science and Engineering, Vellore Institute of Technology,Chennai campus,India 
700 1 |a Kumar, NNithish  |u School of Computer Science and Engineering, Vellore Institute of Technology,Chennai campus,India 
700 1 |a Kumaran, K  |u School of Computer Science and Engineering, Vellore Institute of Technology,Chennai campus,India 
773 0 |t The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings  |g (2024) 
786 0 |d ProQuest  |t Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3153911969/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch