AI SearchArchitectural improvements for the optimization of a time series application
Call Number: AIT ISPR CS no.23-01 Material type:
SeriesSeries: Asian Institute of Technology. Internship Report ; no. CS-23-01Publication details: Pathum Thani, Thailand : Asian Institute of Technology, 2023Description: 48 leaves : illSubject(s): Online resources: Dissertation note: Internship Report (M. Eng.) - Asian Institute of Technology, 2023 Summary: This 6-month internship report highlights the journey of enhancing the architecture of the HOTS application. Commencing in February and concluding in August, the intern ship focused on a primary objective, addressing real-time data handling and optimiz ing data management for larger datasets. To achieve these goals, a streaming service with Apache Kafka was carefully designed and integrated into the HOTS application. Rigorous testing, important feature implementation like the schema registry and conflu ent control center and SSL encryption were integrated, and deployment on a dedicated server resulted in a robust Kafka architecture. Code optimization techniques, includ ing batch processing and improved memory management, were employed to overcome bottlenecks in HOTS. The outcomes showed promising results with significant improve ments in running time, RAM usage, and dataframe sizes. Participation in Smile{u2019}s LLM Hackathon provided valuable insights into real-world LLM applications. The internship fostered valuable experiences in Python development, streaming platform design, and the importance of code optimization. Overall, this report showcases the successful im plementation of architectural improvements for the HOTS application, contributing to a deeper understanding of software engineering and the importance of optimizing code for optimal performance.
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67-Electronic Resource
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Asian Institute of Technology Library Archives | AIT ISPR CS no.23-01 (Browse shelf(Opens below)) | Not for loan |
An Internship Study submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Computer Science
Internship Report (M. Eng.) - Asian Institute of Technology, 2023
This 6-month internship report highlights the journey of enhancing the architecture of the HOTS application. Commencing in February and concluding in August, the intern ship focused on a primary objective, addressing real-time data handling and optimiz ing data management for larger datasets. To achieve these goals, a streaming service with Apache Kafka was carefully designed and integrated into the HOTS application. Rigorous testing, important feature implementation like the schema registry and conflu ent control center and SSL encryption were integrated, and deployment on a dedicated server resulted in a robust Kafka architecture. Code optimization techniques, includ ing batch processing and improved memory management, were employed to overcome bottlenecks in HOTS. The outcomes showed promising results with significant improve ments in running time, RAM usage, and dataframe sizes. Participation in Smile{u2019}s LLM Hackathon provided valuable insights into real-world LLM applications. The internship fostered valuable experiences in Python development, streaming platform design, and the importance of code optimization. Overall, this report showcases the successful im plementation of architectural improvements for the HOTS application, contributing to a deeper understanding of software engineering and the importance of optimizing code for optimal performance.
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