Hi everyone,

We just deployed a new CUDA application (called BRP3) as part of the
einst...@home project. This app roughly up to 75% of a GPU and 3-30% of
a CPU, depending on the GPU model/performance. Thus our scheduler
currently issues these tasks with the following settings:

hu.avg_ncpus = 0.2
hu.ncudas = 1

Please note that BOINC (e.g. sched/sched_customize) revision 22832 is
used in this case.

The problem is that with the settings above BOINC starts CUDA tasks in
addition to CPU tasks that already occupy all existing CPU cores. This
means on a system having four CPU cores and two CUDA devices, four CPU
tasks and two CUDA tasks are launched. Although this behavior is
intended, it doesn't really work out for us because the performance of
the CUDA tasks is degraded significantly - GPU usage goes down to less
than 10%, increasing the runtime by the same factor. Although the CUDA
tasks run with slightly higher priority (below normal on Windows) than
the CPU tasks (low on Windows) they are limited by the already
fully-occupied CPU cores which are still required for up to 30% of the
computation.

Since we couldn't yet release a Linux or Mac OS version we don't know
whether this is a Windows time-slicing issue or not. Are there any other
projects running CUDA tasks in a comparable way?

The only workaround in sight would be to acquire a full CPU core once
again but that's certainly not ideal.

Any ideas are welcome!


Cheers,
Oliver
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