Summary
Objectives:
In our research on brain function analysis, users require two different simultaneous
types of processing: interactive processing to a specific part of data and high-performance
batch processing to an entire dataset. The difference between these two types of processing
is in whether or not the analysis is for data in the region of interest (ROI). In
this study, we propose a Grid portal that has a mechanism to freely assign computing
resources to the users on a Grid environment according to the users’ two different
types of processing requirements.
Methods:
We constructed a Grid portal which integrates interactive processing and batch processing
by the following two mechanisms. First, a job steering mechanism controls job execution
based on user-tagged priority among organizations with heterogeneous computing resources.
Interactive jobs are processed in preference to batch jobs by this mechanism. Second,
a priority-based result delivery mechanism that administrates a rank of data significance.
Results:
The portal ensures a turn-around time of interactive processing by the priority-based
job controlling mechanism, and provides the users with quality of services (QoS) for
interactive processing. The users can access the analysis results of interactive jobs
in preference to the analysis results of batch jobs. The Grid portal has also achieved
high-performance computation of MEG analysis with batch processing on the Grid environment.
Conclusion:
The priority-based job controlling mechanism has been realized to freely assign computing
resources to the users’ requirements. Furthermore the achievement of high-performance
computation contributes greatly to the overall progress of brain science. The portal
has thus made it possible for the users to flexibly include the large computational
power in what they want to analyze.
Keywords
Grid - portal - development framework - region of interest - MEG
