<div dir="auto"><div><div>This sounds like a hypervisor putting all the load on as few cores as possible. But you don't specify what is providing the data. That IO is easily a bottleneck as it's shared across physical and VM. As the datasets are not super huge, make sure you have plenty of RAM on the VM and on 8 separate terminals copy the dataset into a shell variable. Use that as the input for an 8-instance run. The second through eighth instance should load faster as the first takes the hit on libs and code load.</div><div><br></div><div data-smartmail="gmail_signature"><div dir="ltr">-- <br>James P. Kinney III<br><i><i><i><i><br></i></i></i></i>Every time you stop a school, you will have to build a jail. What you
gain at one end you lose at the other. It's like feeding a dog on his
own tail. It won't fatten the dog.<br>
- Speech 11/23/1900 Mark Twain<br><i><i><i><i><br><a href="http://heretothereideas.blogspot.com/" target="_blank">http://heretothereideas.blogspot.com/</a><br></i></i></i></i></div></div><br><div class="gmail_quote gmail_quote_container"><div dir="ltr" class="gmail_attr">On Sun, Apr 27, 2025, 3:47 PM Leam Hall via Ale <<a href="mailto:ale@ale.org">ale@ale.org</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hey all, I'm mildly stumped by a lack of performance issue, and could use insight.<br>
<br>
A friend was running Hyper-V on a Windows laptop, and spun an Ubuntu image with 8 cores to run some Python based analysis on two datasets. The datasets were roughly 150 and 190 MB respectively, and running one command line with & took about three hours. All eight cores were roughly 45% utilized, though with Hyper-V I'm not sure if that's cores assigned to the Ubuntu instance, or on the host machine. There was no memory swapping, and top showed one Python process.<br>
<br>
He wanted things a bit faster, so I suggested opening a second terminal and running the command on each dataset separately, not in series. The load on all 8 cores went up about 15%, there were two Python processes, but the processes still took 3 hours.<br>
<br>
Is this a Hyper-V based issue, or something else?<br>
<br>
Thanks!<br>
<br>
Leam<br>
<br>
-- <br>
Software Engineer (<a href="http://reuel.net/career" rel="noreferrer noreferrer" target="_blank">reuel.net/career</a>)<br>
Scribe: The Domici War (<a href="http://domiciwar.net" rel="noreferrer noreferrer" target="_blank">domiciwar.net</a>)<br>
Coding Ne'er-do-well (<a href="http://github.com/LeamHall" rel="noreferrer noreferrer" target="_blank">github.com/LeamHall</a>)<br>
<br>
Between "can" and "can't" is a gap of "I don't know", a place of discovery. For the passionate, much of "can't" falls into "yet". -- lh<br>
<br>
Practice allows options and foresight. -- lh<br>
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</blockquote></div></div></div>