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The idea is to define how to reduce the total events processed so people can compare results in microbenchmark settings.
1) pick first N files per process
This would reduce the number of files hit by workload, given that all the files are similarly sized nanoAOD, I worry that different process may have very different # of total files. Another problem is reducing # of files may change how some people prefer to parallelize the whole workload
2) pick first N events per file
This hit all the files like the full-version, effectively pretending each file is smaller than they really are. This hits all the files, so it's fairer from specific FS/network considerations. Again because nanoAODs are similarly sized, this should be reasonable. One problem with this approach is opening many many files in itself is a bottleneck, and this approach does not reduce time spent there.
3,4) pick first some% files / events from each process/file
similarly to 1 and 2 except we do it as %. Should be fairer and produce higher fidelity in terms of physics result, but annoying to implement...
The text was updated successfully, but these errors were encountered:
Hi, what's the goal for the micro challenge? I have run smaller-scale versions of the AGC only as a test bed with faster iteration time, using method 1).
ideally "file" -> "histograms" should scale linearly up to very high core/node counts. If someone's implementation doesn't show this, or only show in 1) but not 2), it's a sign something is not efficient
B) help leveling benchmarking ground
it's much easier to manage "1 beefy machine with stable I/O bandwidth and latency" than finding "a cluster with stable occupancy". So that we can benchmark between different setups without reserving a cluster and granting access to every soul out there want to benchmark AGC
The idea is to define how to reduce the total events processed so people can compare results in microbenchmark settings.
1) pick first N files per process
This would reduce the number of files hit by workload, given that all the files are similarly sized nanoAOD, I worry that different process may have very different # of total files. Another problem is reducing # of files may change how some people prefer to parallelize the whole workload
2) pick first N events per file
This hit all the files like the full-version, effectively pretending each file is smaller than they really are. This hits all the files, so it's fairer from specific FS/network considerations. Again because nanoAODs are similarly sized, this should be reasonable. One problem with this approach is opening many many files in itself is a bottleneck, and this approach does not reduce time spent there.
3,4) pick first some% files / events from each process/file
similarly to 1 and 2 except we do it as %. Should be fairer and produce higher fidelity in terms of physics result, but annoying to implement...
The text was updated successfully, but these errors were encountered: