Htop Explained Visually
codeahoy.com
codeahoy.com
One thing not mentioned in the article is you can interact with htop using the mouse, for example clicking on column headers to sort by that column, or selecting a process.
You can get get this mouse support for example by installing the gpm package, which enables the mouse support for the terminal.
The next one on the list is Firefox with 8.5 GB VIRT and 994 MB RES.
By the way, I've got 16 GB of RAM and no swap. Anyway all that empty memory between VIRT and RES doesn't go to swap, it's really virtual.
smem's measures - USS, unqiue set size (unshared pages) and PSS, proportional set size (shared pages divided by their share count, ie. how many tasks share them), are far more accurate and easier to reason about than RSS and VSS.
If I have a process that says it's using 1GB of RES, then you can guarantee there is at least 1GB of physical memory in use. It just might also be in use by other things also reporting their own RES usage.
But hey, everyone likes visual explanations ;)
I like these visual explanations though.
If you have their display enabled htop will divide them down as well.
1.0 = 100% usage of a 1-core system
1.0 = 50% usage of a 2-core system
4.0 = 50% usage of an 8-core system
8.0 = 100% usage of an 8-core system
And IIRC, load average is represented usually as 3 numbers, which are over the last 5, 10, and 15 minutes.1, 5 and 15 minutes is the most common intervals
Load of 0 means idle (nothing to run), load of 1 means e.g. one process running and nothing in the queue.
left_meters=AllCPUs Memory Swap
to be left_meters=CPU Memory Swap
That will replace the default CPU monitor with a single meter for the average across all cores. After that, you'll be able to customize things the standard way by pressing F2 within htop.This stackoverflow has some pointers though: http://superuser.com/questions/806614/how-to-compress-or-hid...
The idea is that you can run embarrassingly parallel workflows without needing to recode for a GPU; just launch processes with appropriate affinities. NERSC has compute clusters with thousands of these beasts. They make astronomers very happy.