These are chat archives for thunder-project/thunder
spark-defaults.confand left the other speculation parameters as default. Supposedly this causes Spark to launch redundant copies of tasks that seem to be completing slowly. I would run a job with, say 320 partitions, see some SSL timeouts, and then Spark would keep launching stages named
stage 1 (retry <n>)with 26 partitions, 2 partitions, then 12 partitions, etc.
thunder-ec2gives you. As you may have found out already,
yumbreaks itself if you upgrade python, which you'll want to do to use the newer versions of IPython and matplotlib. Remember to run the script on the slaves as well!
@npyoung thank you for that script! It will be nice to use seaborn on the cluster.
@freeman-lab I think the addition of sampling rate or units could be useful. It would certainly make it easier to quickly understand the timescales that neural activity may be oscillating over.
I am more than happy to contribute to the documentation - I will take a look at it when I can to see if there is anything I can think of adding.
thunder-ec2launch process? how long roughly does it take to complete? could of course do in parallel on all workers via
setup-notebook), since many of the thunder examples import seaborn.