Filesystems continue to be a major performance bottleneck for many applications across a variety of hardware architectures. Most existing attempts to address this issue, e.g., PVFS, rely upon system resources which are not typically tuned for any specific user application, whereas others rely on special hardware capabilities such as shared-memory.We have developed an MPI-based parallel asynchronous I/O (PAIO) software package which enables applications to balance compute and I/O resources directly. PAIO uses a queueing mechanism to stage the data, sent over in parallel from compute nodes, on the reserved I/O nodes. Because the bandwidth of the inter-processor network greatly exceeds that of the filesystem, significant performance improvements can be achieved under a bursty I/O load provided sufficient memory is available for the I/O nodes. The results of PAIO for typical weather applications on an SGI Altix and other architectures will be reported in a poster board.

Remote sensing projects typically require the collaboration and expertise of professionals from multiple disciplines. In order to motivate and train undergraduate students for future careers and/or education in the field of remote sensing, they should be exposed to remote sensing technologies and concepts throughout their undergraduate studies within their selected majors. This work describes the design and development of a laboratory and Internet-based systems environment that facilitates remote sensing education and research based on cross-institutional resource sharing of lidar instrumentation.