Nflight
11-11-2017, 01:49 PM
GPUGRID: New multicore app and WUs
Dears,
we would like to test our new CPU multicore application for quantum chemistry tasks ("QC"). Since it’s the first time we have a CPU app out, I’ll test the behavior of GPUGRID with a relatively large batch that you will see soon. Workunits are named "*QC309big*".
Here’s some features of the app, in short (subject to change):
* Platform: Linux only for now, generic x64.
* Threads: as many as Boinc decides. I guess it depends on your machine, your preferences, and other running tasks in ways which are obscure to me…
* Run time: about 1 CPU hour per WU (so, shorter if multithreading)
* Credit: computed with the default algorithm (tasks are short, don’t expect much). Bonus mechanism for fast turnaround is still on.
* Known bugs: restarts and checkpoints. This should be mitigated with the “keep in memory when suspended” option. Sorry about that, it’s outside of our control.
* Network behavior: the first time you get a WU of this kind it downloads a Python interpreter (miniconda) and then some open-source packages, and installs them in the project directory. The installation is reused whenever possible.
* Disk usage: could go around 1 GB, perhaps more when tasks are running. Resetting the project should remove everything.
* Memory usage: should be around 1 GB when running.
Depending on the results of this test, we’ll start thinking about other platforms.
Thanks and nice crunching!
Toni
11/10/2017 2:58:07 PM · more (http://www.gpugrid.net/forum_thread.php?id=4649)...
Dears,
we would like to test our new CPU multicore application for quantum chemistry tasks ("QC"). Since it’s the first time we have a CPU app out, I’ll test the behavior of GPUGRID with a relatively large batch that you will see soon. Workunits are named "*QC309big*".
Here’s some features of the app, in short (subject to change):
* Platform: Linux only for now, generic x64.
* Threads: as many as Boinc decides. I guess it depends on your machine, your preferences, and other running tasks in ways which are obscure to me…
* Run time: about 1 CPU hour per WU (so, shorter if multithreading)
* Credit: computed with the default algorithm (tasks are short, don’t expect much). Bonus mechanism for fast turnaround is still on.
* Known bugs: restarts and checkpoints. This should be mitigated with the “keep in memory when suspended” option. Sorry about that, it’s outside of our control.
* Network behavior: the first time you get a WU of this kind it downloads a Python interpreter (miniconda) and then some open-source packages, and installs them in the project directory. The installation is reused whenever possible.
* Disk usage: could go around 1 GB, perhaps more when tasks are running. Resetting the project should remove everything.
* Memory usage: should be around 1 GB when running.
Depending on the results of this test, we’ll start thinking about other platforms.
Thanks and nice crunching!
Toni
11/10/2017 2:58:07 PM · more (http://www.gpugrid.net/forum_thread.php?id=4649)...