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BigPanDA@Titan Implementation Plan Notes
Sarp Oral
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Task 3.4 implantation plan notes
Following list focuses on file system and I/O pieces, specifically parallel file system access contention; file system performance resulting from heavy loads; and communication network (titan-spider 2) contention topics. These are covered in the numbered list in task 3.4 as: #3, “Monitor the impact of the I/O associated with the PanDA-enabled payloads on the wider Titan I/O performance)” and #4 “Quantify the marginal increase in network contention on Titan’s interconnection network”.
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Specific tasks planned
Using the GUIDE interface (guide.ccs.ornl.gov), obtain the list of all PanDA jobs executed for last weeks. Status: Completed. The query is written and provides the list of past PanDA jobs for any time duration. On average, we observe more than 3,000 PanDA jobs executed in a two-week period. Feed the PanDA job list to the Job I/O query in GUIDE and automate the process. This will provide per PanDA job data written and read, average I/O size, and OST usage in 5 minute intervals. Status: In progress. Current mechanism is manual and labor intensive. Need to write a Python script to automate. Dump the Job I/O query in step 2 to a flat file in a matrix format for post processing. Status: Not yet started.
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Specific tasks planned, continued
Statistically analyze the data obtained in step 3 to classify and identify the PanDA I/O characteristics. Status: Not yet started. Correlate the data from step 4 to Spider 2 file system I/O data and identify the impact of PanDA I/O on the file system. Identify the start and stop times of jobs documented in step 1 and feed and correlate the data with the the GUIDE Titan LNET Router activity. Currently this process in manual and labor intensive. Need to write a Python script to automate the process. Status: Not yet started. Statistically analyze the data obtained in step 6 and identify the possible Titan I/O interconnect contention. Status: Not eyet started.
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