Hi. This issue is being discussed in
https://github.com/JuliaLang/julia/issues/15467 On Wednesday, March 16, 2016 at 11:12:21 AM UTC-3, Páll Haraldsson wrote: > > Interesting, this *seems* like a bug, since you only did a minor update. > *Maybe* this isn't a problem and there is some space-time trade-off (that I > would have more expected with a major update). Is the program at least not > slower? > > I do not recall with Windows, is memory consumption in the Task Manager, > really a good indication? Could it be memory that is "allocated", but > actually does not slow down at all, is just virtual memory that is not > "used", maybe even not initialized? > > Is this not a problem without @parallel? > > -- > Palli. > > On Wednesday, March 9, 2016 at 7:30:19 PM UTC, Eduardo Lenz wrote: >> >> Hi. >> >> Running the same code with Julia 0.4.3 and with julia 0.4.0, I observed >> the following memory usage (figure below). The beginning is related to the >> code running in Julia 0.4.0, then, the process is canceled (memory drops) >> and the same code is executed with Julia 0.4.3. As one can see in this >> picture, at each iteration of the algorithm (wich uses an @parallel for) >> there is a systematic increase in memory usage. In a latter post I stated >> that it didn't happen in windows, just Linux, but it is not true, >> since these examples were performed in a windows machine. I don´t know if >> it is related to some change in gc(), but I tested >> calling gc() after each iteration of the algorithm and it did not changes >> the observed behaviour. >> >> >> >> <https://lh3.googleusercontent.com/-VtRnSBrROdQ/VuB3zoXedYI/AAAAAAAAQYQ/uHcqiD_tYO4/s1600/processos.png> >> >
