THE ASIAN BULLETIN OF BIG DATA MANAGMENT Vol. 4. Issue 1 (2024) https://doi.org/10.62019/abbdm.v4i1.112 139 Scratchpad Memory Management Random Sampling Algorithm for Multi-core Processor Kavita Tabbassum, Shahnawaz Farhan Khahro, Saima Shaikh, Farah Naveen Issani, Suhni Abbasi, Hina Chandio Chronicle Abstract Article history Received: February 12, 2024 Received in the revised format: Feb 24, 2024 Accepted: Feb 28, 2024 Available online: March 01, 2024 Traditional compiler-based SPM management often fails to accurately predict the memory access characteristics of system scheduling and task switching in a Multi-core Processor environment, thus affecting the effect of SPM management. The use of runtime dynamic detection can make up for this flaw and provide an accurate and efficient dynamic management method. This research focuses on the analysis of the similarities and differences between SPM management in Multi-core Processor environment and single-task environment, and builds a real-time operating system (RTOS) supporting multi-task scheduling according to experimental requirements, which is necessary for the random sampling of SPM allocation algorithm and improvements to meet the needs of adaptive SPM allocation for program runtime in a Multi-core Processor environment. The activity of the random sampling algorithm in Multi-core Processor environment is analysed which proves the effectiveness of the allocation algorithm for Multi-core Processor environment. Kavita Tabbassum, Shahnawaz Farhan Khahro, Saima Shaikh, Farah Naveen Issani, Suhni Abbasi and Hina Chandio are currently affiliated with the Department of Information Technology Center, Sindh Agricultural University Tandojam, 70060, Pakistan. Email: kavita@sau.edu.pk Email: shahnawazfarhan@gmail.com Email: suhni.abbasi@sau.edu.pk Email: Farahnaveenissani@gmail.com Email: ss2kcs@gmail.com Email: hinashafi@sau.edu.pk *Corresponding Author* Keywords: Core-working Set, Memory Management, Multi-core Processor, On- chip Memory, Scratchpad Memory. © 2024 © 2024 Asian Academy of Business and social science research Ltd Pakistan. All rights reserved INTRODUCTION In this paper, we present a comprehensive analysis of scratchpad memory (SPM) management in the context of multi-core processor environments. Our objective is to address the limitations of traditional compiler-based SPM management by proposing a dynamic and adaptive approach that can effectively handle the complexities of memory access patterns in multi-core systems. The significance of our proposed architecture lies in its ability to overcome the challenges posed by system scheduling and task switching in multi-core environments. By leveraging runtime dynamic detection techniques, we aim to provide a more accurate and efficient method for SPM management, thereby optimizing memory utilization and enhancing overall system performance. Through this study, we seek to highlight the importance of adaptive SPM allocation strategies in modern computing systems and demonstrate the potential benefits of our approach in improving memory access efficiency in multi-core processor setups. Traditional compiler-based SPM management often fails to accurately predict the memory access characteristics of system scheduling and task switching in a Multi- core Processor environment, thus affecting the effect of SPM management. The use of runtime dynamic detection can make up for this flaw and provide an accurate and efficient dynamic management method. This research focuses on the analysis of the