Research Characterization on I/O Improvements of Storage Environments

Nowadays, it has being verified some interesting improvements in I/O architectures. This is an essential point to complex and data intensive scalable applications. In the scientific and industrial fields, the storage component is a key element, because usually those applications employ a huge amount of data. Therefore, the performance of these applications commonly depends on some factors related to time spent in execution of the I/O operations. In this paper we present a research characterization on I/O improvements related to the storage targeting high-performance computing (HPC) and data-intensive scalable computing (DISC) applications. We also evaluated some of these improvements in order to justify their concerns with the I/O layer. Our experiments were performed in the Grid’5000, an interesting testbed distributed environment, suitable for better understanding challenges related to HPC and DISC applications. Results on synthetic I/O benchmarks, demonstrate how to improve the performance of the latency parameter for I/O operations.