An effort to characterise enhancements I/O of storage environments. (17th March 2023)

• Record Type: Journal Article
• Authors: Pioli, Laercio; Ströele, Victor; Dantas, Mario A.R.
• Is Part Of: International journal of grid and utility computing. Volume 14:Number 1(2023)
• Page Start: 51
• Page End: 61
• Publication Date: 2023-03-17
• Subjects: I/O characterisation -- I/O performance -- I/O improvement -- I/O model -- HPC -- DISC -- Big Data -- GRID5000 -- storage system -- storage environments; Electronic data processing -- Distributed processing -- Periodicals; Electronic commerce -- Management -- Computer programs -- Periodicals; 004.605
• Languages: English
• ISSNs: 1741-847X

Abstract

Data management and storage are becoming challenging nowadays due to the huge amount of created, processed, and stored data. The growing gap between power processing and storage latency increases this performance disparity. Targeting reducing I/O bottleneck in storage environments, researchers are proposing interesting improvements in I/O architectures. High-Performance Computing (HPC) and Data-Intensive Scalable Computing (DISC) applications are kinds of such systems that are faced with data challenges due to the need to deal with many parameters when managing data. This study describes our characterisation model for classifying research works on I/O performance improvements for storage systems and devices that improve HPC and DISC overall application performance. We present a set of experiments using a synthetic I/O benchmark performed inside the Grid'5000. We show that the latency when performing I/O operations can undergo many variations if we take into account the presented factors evaluated in the experiments.