The difficulties faced by scientists and engineers in attaining high performance I/O for data-intensive applications are exacerbated by the low level of abstraction presented by current I/O systems. Proposed research will create higher level I/O abstractions for developers. The proposed SSDS framework models I/O as I/O Graphs that `connect' application components with input or output mechanisms like file systems based on metadata constructed offine by autonomous metabots. I/O Graphs can be programmed to realize application-specific I/O functionality, such as data filtering and conversion, data remeshing, and similar tasks. Their management is automated, including the mapping of their logical graph nodes to underlying physical MPP and distributed machine resources. I/O performance in SSDS will be improved by integrating the computational I/O actions of I/O Graphs with the backend file systems that store high volume data and with the I/O actions already taken by applications, and by moving metadata management offline into metabots. The implementation of the SSDS system and its I/O Graph model will impact a substantial HPC user community, due to its planned integration with the Lightweight File System (LWFS) currently under development at Sandia National Laboratories (SNL). This file system and its SSDS extensions will be deployed on large-scale machines at Sandia to demonstrate scalability and application utility. SSDS will be integrated with the file formats and file systems used by other groups at Sandia and at Oak Ridge National Laboratories (ORNL)
