Study of data distribution strategies for parallel I/O management
Recent studies have demonstrated that significant I/O operations are performed by a number of different classes of parallel applications. Appropriate I/O management strategies are required however for harnessing the power of parallel I/O. This paper focuses on two I/O management issues that affect system performance in multiprogrammed parallel environments. Characterization of the I/O behavior of parallel applications in terms of four different models is discussed first, followed by an investigation of the performance of a number of different data distribution strategies. Using computer simulations, this research shows I/O characteristics of applications and data distribution have an important effect on system performance. Applications which can simultaneously do computation and I/O, plus strategies that can incorporate centralized I/O management are found to be beneficial for a multiprogrammed parallel environment.
Kwong, P. (Peter), & Majumdar, S. (1996). Study of data distribution strategies for parallel I/O management.