Project Details

Description

Conventional solutions for I/O have attempted to provide hardware

and software parallelism via RAIDs or parallel machines/supercomputers.

However, the problems associated with cost, scalability,

and/or accessibility of these environments make them unattractive

for widespread usage. This research addresses this important

deficiency in high-performance I/O support, by proposing a shared storage

system using an off-the-shelf cluster of workstations, disks, and

networks. The proposed research goes beyond current state-of-the-art in I/O

support for clusters and examines a broad spectrum of

issues related to I/O software on clusters, that include

application-directed, compiler-directed, and runtime system-directed

optimizations. These optimizations are crucial to reduce/hide the

latencies to different levels of the I/O hierarchy which will help

accelerate the deployment of clusters for I/O-intensive applications.

StatusFinished
Effective start/end date8/1/017/31/05

Funding

  • National Science Foundation: $239,527.00

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