In Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy
Will defend his PhD dissertation
The increasing number of cores per node has propelled the performance of leadership scale systems from teraflops to petaflops. On the other hand, bandwidth of I/O subsystems have almost been stagnant. This has created a huge gap between the computational and I/O time, making I/O a major bottleneck. Furthermore, the realized I/O bandwidth in such systems is in general far lower compared to their theoretical peak bandwidth. The Message Passing Interface (MPI) has been the de-facto standard for parallel computing in the past couple of decades. MPI-I/O, which is a part of the MPI specification, not only offers a clean approach to access the file system from the application but also acts as a middle-ware between the application and the file system to specify a variety of enhancements. Specifically, collective I/O has proven to be very effective for I/O in large scale systems and helps to bridge the gap between the theoretical and sustained I/O bandwidth. This dissertation aims at developing approaches to improve parallel I/O at this level. In particular this dissertation investigates methods to utilize data-layout aware rank assignment to improve I/O performance, overlap collective I/O with computation and finally use the principles of collective I/O and apply them to a staging based I/O architecture.
Date: Friday, November 8, 2013
Time: 2:30 PM
Place: PGH 550
Faculty, students, and the general public are invited.
Advisor: Prof. Edgar Gabriel