Embarrassingly Parallel Time Series Analysis for Large Scale Weak Memory Systems
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Re: Embarrassingly Parallel Time Series Analysis for Large Scale Weak Memory Systems
#2Well, I would have prefered a first year student demonstrating the trivia that operation like sorting multidimensional vector will kick by the nature less optimization possible in CPU and GPU and that non linear operation requires reading the whole sample to have a non random quantifiable error.
Hence, map reduce performance is better for combination of distributive linear operation (like ARMA, and I still wonder about hilbertian geometry) and horrible for non linear mapped functions (median filter, nth percentile, sort, top X).
Re: Embarrassingly Parallel Time Series Analysis for Large Scale Weak Memory Systems
#3Re: Embarrassingly Parallel Time Series Analysis for Large Scale Weak Memory Systems
#4I skimmed through the paper. It's packed with formulas and technical details. I can't judge if it's a relevant contribution to the subject but... the title. Do they need that to be noticed? Just imagine "Embarrassingly Fast Electromagnetic Waves but not any Faster" instead of "On the Electrodynamics of Moving Bodies" (Zur Elektrodynamik bewegter Körper) http://.ca/wiki/Zur_Elektrodynamik_bewegter_Körper
Re: Embarrassingly Parallel Time Series Analysis for Large Scale Weak Memory Systems
#5I skimmed through the paper. It's packed with formulas and technical details. I can't judge if it's a relevant contribution to the subject but... the title. Do they need that to be noticed? Just imagine "Embarrassingly Fast Electromagnetic Waves but not any Faster" instead of "On the Electrodynamics of Moving Bodies" (Zur Elektrodynamik bewegter Körper) http://.ca/wiki/Zur_Elektrodynamik_bewegter_Körper
"Embarrassingly parallel" isn't a term that they invented: https://en.wikipedia.org/wiki/Embarrassingly_parallel