Final Report
Multicore-Based Disks for Data-Intensive Computing (2009 - )
Training and Development
3.1 Student Support
This project has directly supported about 8 students including 6 doctoral students and 2 undergraduate students. The project also indirectly contributed to approximately 17 graduate students who took the COMP7500 (i.e., Advanced Operating systems) class and 65 undergraduate students.
The following 6 doctoral students have been partially supported by this NSF grant in year 1 (i.e., 2009-2010):
The following 9 doctoral/master’s students have been partially supported by this NSF grant in year 2 (i.e., 2010-2011):
The following 2 undergraduate students have been partially supported by this NSF grant in year 1 (i.e., 2009-2010):
Figure 33: Our undergraduate research assistants helped in building a cluster system.
The following 4 undergraduate students have been partially supported by this NSF grant in year 2 (i.e., 2010-201a):
Figure 34: The cluster computing system built by our undergraduate research assistants.
3.2 Research Experience for Undergraduate Students
To recruit new undergraduate students, especially women and minorities, to conduct research
in the area of storage systems, we designed a research program that offers ample
opportunity to undergraduate students to do intensive research in data-intensive computing
with the PIs. In particular, students and the PIs are brought together to conduct research
experiments in the field of high-performance storage systems. The photo below shows two
undergraduate students - Tsukasa Ogihara (right) and Joshua Lewis (middle) - are building
a cluster computing system using commodity-off-the-shelf (COTS) hardware components.
The cluster system (see Figs. 33 and 34) built by our undergraduate research assistants
will be used as a high-performance computing platform to support our computer security
education. The cluster recently build in our department at Auburn supports security middleware
services for secure software applications. We will use this cluster computing platform
to design and implement study how to improve software application’s quality-of-security
without adversely affecting performance.
3.3 Contributions to Courses
This project has directly and indirectly contributed to the following classes: