Parallelization and characterization of data-intensive applications
the goal of this project is to find out it takes to achieve good
I/O performance for real-life data-intensive tasks on parallel machines
suitable for I/O.
Interprocedural compiler analysis for overlapping large I/O operations with
computation the goal of this project is to schedule large I/O
operations which are beyond the capacity of standard operating
system prefetch and write-behind.
Scheduling and resource management for I/O intensive tasks on peer-to-peer
systems the goal of this project is to develop techniques
for achieving high performance for I/O intensive tasks on peer-to-peer
systems.
Data placement techniques for multidimensional datasets on large disk farms
the goal of this project is to develop data placement techniques
for multidimensional datasets both across multiple disks and within
individual disks to minimize query response time.