Alok Choudhary [email protected] 1Northwestern University
Access Patterns, Metadata, and Performance
Alok Choudhary and Wei-Keng LiaoDepartment of ECE, Northwestern University
Collaboration with ANL
SDM kickoff meeting
July 10-11, 2001
Alok Choudhary [email protected] 2Northwestern University
Virtuous Cycle
Problem setup(Mesh, domainDecomposition)
Simulation(Execute app,Generate data)
Manage,Visualize, Analyze
Measure Results,Learn, Archive
Alok Choudhary [email protected] 4Northwestern University
Data Access Sequence Dependency
• Temporal dependency– Access the same data set at
different time stamp
• Spatial dependency– Access different data sets at the
same time stamp
• Resolution dependency– Access the same data set at different
resolution
• Sequence is useful for I/O performance improvement, eg. Pre-fetch, pre-stage, storage continuity
Alok Choudhary [email protected] 5Northwestern University
Spatial Data Access Patterns
• Parallel partition patterns:– Regular, irregular
– Static, dynamic during simulation
• Access sequence– Spatial, temporal, resolution
• Access frequency– Once only, multiple times (overwrite for restart)
• Access amount– Large, medium, small chunks
Alok Choudhary [email protected] 6Northwestern University
Access Patterns for Visualization/Analysis
• Generated from real data during simulation or in post-simulation process
• Smaller size than real data– Type conversion,
eg. float unsign char
– Reduce/increase resolution
– Projection 3D to 2D
• 3 types of data generate and display sequence
Alok Choudhary [email protected] 7Northwestern University
Architecture
UserApplications
MDMS
Storage Systems(I/O Interface)
SimulationData AnalysisVisualization
Metadataaccess pattern, history
MPI-IO(Other interfaces..)
QueryInput MetadataHints, Directives
Associations OIDsparameters for I/O
Schedule, Prefetch, cacheHints (coll I/O)
Performance InputSystem metadata
I/O func (best_I/O (for these param))Hint
Data
Alok Choudhary [email protected] 8Northwestern University
Approach
• Management meta data using OR-DBMS– Collect and organize meta data in relation tables– Design meta data query interface using SQL
• Access to HSS– Obtain current storage layout, configuration– Native I/O interfaces or MPI-IO
• I/O optimization– Determine optimal I/O calls– Overlap I/O with computation, communication, and I/O– Pre-fetch, pre-stage, migrate, purge in HSS– Sub-filing for large file, file container for small files
Alok Choudhary [email protected] 10Northwestern University
Metadata
• Application Level– Algorithms, compiling, execution environments
– Time stamps, parameters, result summary
• Programming Level– Data types, structures, association of datasets, partition patterns
• Storage System Level– File locations, file structure, I/O modes, host names, device types,
path names, storage hierarchy
• Performance Level– I/O bandwidth of HSS for local and remote access
– Data access sequence, frequency, other access hints
– Collective or non-collection I/O
Alok Choudhary [email protected] 11Northwestern University
Applications
• Asto3D -- study the highly turbulent convective
layers of late-type star – Write only
– regular partition on all data sets
• ENZO -- simulate the formation of a cluster of
galaxies consisting of gas and stars– Both read and write
– Both regular and irregular partition
– Adaptive Mesh Refinement dynamic load balancing
• Common feature– Checkpoint / restart
– Post-simulation data analysis
– Visualizing the process of the computation in the form of a movie
Alok Choudhary [email protected] 12Northwestern University
Interface
Alok Choudhary [email protected] 13Northwestern University
Run Application
Alok Choudhary [email protected] 14Northwestern University
Dataset and Access Pattern Table
Alok Choudhary [email protected] 15Northwestern University
Data Analysis
Alok Choudhary [email protected] 16Northwestern University
Integrating Analysis
Problem setup(Mesh, domainDecomposition)
Simulation(Execute app,Generate data)
Manage,Visualize, Analyze
Measure Results,Learn, Archive
On-line analysisAnd mining
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