HECURA: Concurrent I/O Management for Cluster-based Parallel Storages

University Of Rochester, Rochester NY

Investigators

Abstract

This project investigates system-level techniques to efficiently support concurrent I/O workloads on cluster-based parallel storages. At the server operating system level, research will focus on the reduction of disk seek/rotation overhead during concurrent I/O. At the storage cluster level, research will focus on the synchronization within each parallel I/O operation under concurrent workloads. For parallel I/O embedded with computing tasks (like parallel data aggregation), research will be performed on storage server load adaptation under concurrent workloads. Efforts will be made to integrate proposed techniques with the server operating system, clusterbased parallel file system, and I/O middleware. The resulted software should be transparent to parallel I/O applications so they can benefit without any changes.