Comments (6)
Why does it need to be one job at a time on each machine?
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I think that we discussed that this would be the "simpler" option. There's no reason why we wouldn't want to eventually make use of all cores.
from tango.
We could make use of all cores by simply "prealloc'ing" one docker instance
for each core.
On Saturday, March 28, 2015, Jake Zimmerman [email protected]
wrote:
I think that we discussed that this would be the "simpler" option. There's
no reason why we wouldn't want to eventually make use of all cores.—
Reply to this email directly or view it on GitHub
#52 (comment).
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I don't think there's an analog to prealloc in Docker. If you have a job
with Docker, you just run it; there's no need to prealloc.
On Sat, Mar 28, 2015 at 11:50 PM droh [email protected] wrote:
We could make use of all cores by simply "prealloc'ing" one docker instance
for each core.On Saturday, March 28, 2015, Jake Zimmerman [email protected]
wrote:I think that we discussed that this would be the "simpler" option.
There's
no reason why we wouldn't want to eventually make use of all cores.—
Reply to this email directly or view it on GitHub
#52 (comment).Sent from my iPhone.
—
Reply to this email directly or view it on GitHub
#52 (comment).
from tango.
The Tango scheduler, which is independent of any particular vmms, is designed
around the idea of matching a job with a free instance. So to get the same
behavior as our current Tashi system, we would simply prealloc 40 (5
backend servers x 8 cores per sever) and then round robin schedule.
On Saturday, March 28, 2015, Jake Zimmerman [email protected]
wrote:
I don't think there's an analog to prealloc in Docker. If you have a job
with Docker, you just run it; there's no need to prealloc.On Sat, Mar 28, 2015 at 11:50 PM droh <[email protected]
javascript:_e(%7B%7D,'cvml','[email protected]');> wrote:We could make use of all cores by simply "prealloc'ing" one docker
instance
for each core.On Saturday, March 28, 2015, Jake Zimmerman <[email protected]
javascript:_e(%7B%7D,'cvml','[email protected]');>
wrote:I think that we discussed that this would be the "simpler" option.
There's
no reason why we wouldn't want to eventually make use of all cores.—
Reply to this email directly or view it on GitHub
#52 (comment).Sent from my iPhone.
—
Reply to this email directly or view it on GitHub
#52 (comment).—
Reply to this email directly or view it on GitHub
#52 (comment).
Sent from my iPhone.
from tango.
The PR for this: #69
from tango.
Related Issues (20)
- support for docker resource control
- distDocker:getImages needs to check timeouts
- distDocker:getImages is not useful
- jobs with high ids stay waiting when the job id counter rolls over HOT 2
- running jobs should report time elapsed since last state change
- 'NoneType' object has no attribute '__getitem__' in jobManager.py
- NUM_THREADS not used
- Call to VMMS localDocker failed
- VM jobs run indefinitely HOT 13
- Autograding. Error message: 795: unexpected token at '---' HOT 3
- No more output after changing autograding-image to ubuntu:18.04 HOT 1
- Code improvement opportunities HOT 1
- Tango concurrency and locking issues HOT 5
- Better and more unit tests
- Fix pylint issues
- Type annotations
- Unneeded requirements
- clients/tango-cli.py can't be run without throwing exceptions HOT 2
- Path to Python interpreter is hard-coded in tango-cli.py
- Add way to preserve completed job lists
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