Hi,
Our own installation guide does advise against OpenCL on NVIDIA hardware,
and also hints that compiler compatibility is dependent on the CUDA
version, but we could improve the latter I think.
Last time we considered performance of OpenCL on NVIDIA, the GPU kernels
seemed to always run
Thank you for this workaround!
Just setting the GMX_DISABLE_GPU_TIMING environment variable has
allowed mdrun to progress for several million steps. The memory usage
is still high at about 1 GB memory and 26 GB swap, but it does not
appear to increase as the simulation progresses.
I tried 6
Hi,
This is an issue I noticed recently, but I thought it was only
affecting some use-cases (or some runtimes). However, it seems it's a
broader problem. It is under investigation, but for now it seems that
eliminate it (or strongly diminish its effects) by turning off
GPU-side task timing. You
Hi,
There's too little information for us to guess where the problem could be -
mdrun could be leaking memory, or it could be an issue where the
driver/runtime are also doing it.
Since you're using a version of gcc you compiled/installed yourself, do
yourself a favour and get a version that's
Hello!
I'm trying to run molecular dynamics on a fairly large system
containing approximately 25 atoms. The simulation runs well for
about 10 steps and then gets killed by the queueing engine due to
exceeding the swap space usage limit. The compute node I'm using has
12 cores in two
