TY - GEN
T1 - Using semantic information to guide efficient parallel I/O on clusters
AU - Schulz, M.
N1 - Publisher Copyright:
© 2002 IEEE.
PY - 2002
Y1 - 2002
N2 - Despite the large I/O capabilities in modern cluster architectures with local disks on each node, applications mostly are not enabled to fully exploit them. This is especially problematic for data intensive applications which often suffer from low I/O performance. As one solution for this problem, a distribution I/O management (DIOM) system has been developed to manage a transparent distribution of data across cluster nodes and to then allow applications to access this data purely from local disks. In order to be effective, however, this distribution process requires semantic information about both the application and the input data. This work therefore extends DIOM to include independent specifications for both data formats and application I/O patterns and thereby decouples them. This work is driven by an application from nuclear medical imaging, the reconstruction of PET images, for which DIOM has proven to be an adequate solution enabling truly scalable I/O and thereby improving the overall application performance.
AB - Despite the large I/O capabilities in modern cluster architectures with local disks on each node, applications mostly are not enabled to fully exploit them. This is especially problematic for data intensive applications which often suffer from low I/O performance. As one solution for this problem, a distribution I/O management (DIOM) system has been developed to manage a transparent distribution of data across cluster nodes and to then allow applications to access this data purely from local disks. In order to be effective, however, this distribution process requires semantic information about both the application and the input data. This work therefore extends DIOM to include independent specifications for both data formats and application I/O patterns and thereby decouples them. This work is driven by an application from nuclear medical imaging, the reconstruction of PET images, for which DIOM has proven to be an adequate solution enabling truly scalable I/O and thereby improving the overall application performance.
KW - Biomedical image processing
KW - Biomedical imaging
KW - Detectors
KW - Image reconstruction
KW - Image storage
KW - Middleware
KW - Operating systems
KW - Personal communication networks
KW - Positron emission tomography
KW - Resource management
UR - http://www.scopus.com/inward/record.url?scp=84949230673&partnerID=8YFLogxK
U2 - 10.1109/HPDC.2002.1029911
DO - 10.1109/HPDC.2002.1029911
M3 - Conference contribution
AN - SCOPUS:84949230673
T3 - Proceedings of the IEEE International Symposium on High Performance Distributed Computing
SP - 135
EP - 142
BT - Proceedings - 11th IEEE International Symposium on High Performance Distributed Computing, HPDC 2002
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th IEEE International Symposium on High Performance Distributed Computing, HPDC 2002
Y2 - 24 July 2002 through 26 July 2002
ER -