A number of new network storage architectures have emerged recently that provide shared, adaptable and high-performance storage systems for dataintensive applications. Three common storage networking architectures are Direct-Attached Storage (DAS), Network-Attached Storage (NAS), and Storage Area Network (SAN). Efficient implementations of each of these classes of storage architecture can have a significant impact on overall system performance. To be able to tune both the performance of a network storage architecture and its underlying workload, an accurate simulation modeling environment can be very valuable. In this paper we present ParIOSim, a validated execution-driven simulator for network storage systems. This simulator can be used to accurately predict the performance of parallel I/O applications as a function of the underlying storage architecture. ParIOSim also provides a flexible simulation environment to guide system level storage optimizations. To evaluate the accuracy of ...
Yijian Wang, David R. Kaeli