Update GPU groups/names

rm/slurm/gpus.rst

@@ -6,37 +6,38 @@ flavors of Nvidia GPUs attached to them to be used with CUDA-enabled code.
 
 Right now we have these nodes available:
 
-======== =============== ====== ===== =========
-Nodename GPU Type        Memory Count Partition
-======== =============== ====== ===== =========
-gpu-1    GTX 1080 TI     12 GB  2     test
--------- --------------- ------ ----- ---------
-gpu-2    GTX 1080        8 GB   3     gpu
--------- --------------- ------ ----- ---------
-gpu-3    GTX 1080        8 GB   3     gpu
--------- --------------- ------ ----- ---------
-gpu-4    Quadro RTX 5000 16 GB  4     gpu
--------- --------------- ------ ----- ---------
-gpu-5    Quadro RTX 5000 16 GB  4     gpu
--------- --------------- ------ ----- ---------
-gpu-6    Quadro RTX 5000 16 GB  4     gpu
--------- --------------- ------ ----- ---------
-gpu-7    Quadro RTX 5000 16 GB  4     gpu
-======== =============== ====== ===== =========
+======== =============== ====== ===== ========= ============
+Nodename GPU Type        Memory Count Partition Architecture
+======== =============== ====== ===== ========= ============
+gpu-1    GTX 1080 TI     12 GB  2     test      Pascal
+-------- --------------- ------ ----- --------- ------------
+gpu-2    GTX 1080        8 GB   3     gpu       Pascal
+-------- --------------- ------ ----- --------- ------------
+gpu-3    GTX 1080        8 GB   3     gpu       Pascal
+-------- --------------- ------ ----- --------- ------------
+gpu-4    Quadro RTX 5000 16 GB  4     gpu       Turing
+-------- --------------- ------ ----- --------- ------------
+gpu-5    Quadro RTX 5000 16 GB  4     gpu       Turing
+-------- --------------- ------ ----- --------- ------------
+gpu-6    Quadro RTX 5000 16 GB  4     gpu       Turing
+-------- --------------- ------ ----- --------- ------------
+gpu-7    Quadro RTX 5000 16 GB  4     gpu       Turing
+======== =============== ====== ===== ========= ============
 
-Both the 12GB 1080 TI and the 8GB 1080 are grouped under the name **1080**. The
-short name for the more powerful Quadro cards is **rtx5k**.
+Both the 12GB 1080 TI and the 8GB 1080 are grouped under the name **pascal**. The
+short name for the more powerful Quadro cards is **turing**.
 
 To request any GPU, you can use ``-p gpu --gres gpu:1`` or ``-p test --gres
 gpu:1`` if you want to test things. The ``gres`` parameter is very flexible and
-allows to request the GPU group (**1080** or **rtx5k**).
-For example, to request 2 Geforce 1080, use ``--gres gpu:1080:2``. This will
+allows to request the GPU group/architecture (**pascal** or **turing**).
+For example, to request 2 Geforce 1080, use ``--gres gpu:pascal:2``. This will
 effectively hide all other GPUs and grants exclusive usage of the devices.
 
 You can use the `nvidia-smi` tool in an interactive job or the node-specific
 charts to get an idea of the device's utilization.
 
-Any code that supports CUDA up to version 10.1 should just work out of the box, that includes python's pygpu or Matlab's gpu-enabled libraries.
+Any code that supports CUDA up to version 10.1 should just work out of the box,
+that includes python's pygpu or Matlab's gpu-enabled libraries.
 
 .. note::
 
@@ -44,12 +45,15 @@ Any code that supports CUDA up to version 10.1 should just work out of the box,
     container**. You have to pass the ``--nv`` flag to any
     singylarity calls, however.
 
-Example: Request an interactive job (srun --pty) with 4 cores, 8gb of memory and a single card from the rtx5k group. Instead of ``/bin/bash`` we use the shell from a singularity container and tell singularity to prepare an nvidia environment ``singularity shell --nv``:
+Example: Request an interactive job (``srun --pty``) with 4 cores, 8 GB of
+memory and a single card from the *turing* group. Instead of ``/bin/bash`` we use
+the shell from a singularity container and tell singularity to prepare an
+Nvidia environment with ``singularity shell --nv``:
 
 .. code::
 
-   srun --pty -p gpu --gres gpu:rtx5k:1 -c 4 --mem 8gb \
-     singularity shell --nv /data/container/unofficial/fsl/fsl-6.0.3.sif
+   srun --pty -p gpu --gres gpu:turing:1 -c 4 --mem 8gb \
+     singularity shell --nv /data/container/unofficial/fsl/fsl-6.0.4.sif
 
    Singularity> hostname
    gpu-4