Performance Analysis of Existing Storage and Processing Systems (Survey Paper)

Abstract

Enhancing the effectiveness and scalability of present-day computer systems requires performance study and enhancement of existing storage and processing hardware, soft- ware and their connections between them in order to effectively utilize them. The performance analysis methodologies, strategies, and case studies as they pertain to storage and processing devices are covered in great detail in this survey report. The objective is to comprehend the variables affecting system performance, detect performance bottlenecks, and suggest efficient optimization tech- niques. An overview of the significance of performance analysis in the present-day technological landscape introduces the paper. It draws attention to how quickly data must be processed, how much data must be stored, and how effectively resources must be used. The necessity to overcome these obstacles and realize the full potential of storage and processing devices served as the impetus for this survey. In-depth analysis of the various perfor- mance measures for assessing storage and processing systems is provided in the survey report. IOPS (Input/output Operations Per Second) and other important metrics are explained in detail. The importance of workload characterization and comparison as important methods for performance analysis are also covered in the paper. Bench-marking enables systematic comparison and as- sessment of various devices or configurations, whereas workload characterization includes understanding the nature of the jobs and data patterns that the system processes. The performance analysis techniques are carefully analyzed. Simulators are one of these approaches; they offer a controlled and virtual environment for assessing system performance. Researchers may simulate various workloads and evaluate the behavior of storage and processing devices under different situations using simulators like MQ-Sim and Gem5. The significance of precise as well as realistic simulations is emphasized in the paper in order to produce outcomes in performance analysis that can be trusted. The study also includes case studies that highlight how performance analysis methods are applied in real-world situations. These case studies address a variety of topics, including machine learning, scientific computing, data analytics, and database management systems. The issue statement, the approach used, and the out- comes are all thoroughly examined in each case study. For system architects and developers looking to optimize storage and processing devices in their respective sectors, these insights provide invaluable lessons. In conclusion, this survey report serves as a comprehensive guide to the field of performance analysis and improvement for existing storage and processing devices. By exploring various performance metrics, evaluation methodologies, and real-world case studies, the report provides a deep understanding of the challenges and opportunities in optimizing system performance. The findings presented in this report will be valuable to researchers, practitioners, and industry professionals seeking to enhance the performance of storage and processing devices in diverse application domains.