diff --git a/docs.it4i/general/slurmtopbs.md b/docs.it4i/general/slurmtopbs.md
deleted file mode 100644
index 6ed722114545851512f96f0bcf6ce2f1bbd6a77e..0000000000000000000000000000000000000000
--- a/docs.it4i/general/slurmtopbs.md
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@@ -1,50 +0,0 @@
-# Migrating From SLURM
-
-SLURM-optimized parallel jobs will not run under PBS out of the box.
-Conversion to PBS standards is necessary. Here we provide hints on how to proceed.
-
-It is important to notice that `mpirun`  is used here as an alternative to the `srun` in SLURM. The `-n` flag is used to regulate the number of tasks spawned by the MPI. The path to the script being run by MPI must be absolute. The script rights should be set to allow execution and reading.
-
-The PBS provides some useful variables that may be used in the jobscripts
-`PBS_O_WORKDIR` and `PBS_JOBID`. For example:
-
-The `PBS_O_WORKDIR` returns the directory, where the `qsub` command was submitted.
-The `PBS_JOBID` returns the numerical identifier of the job.
-The `qsub` always starts execution in the `$HOME` directory.
-
-## Migrating PyTorch From SLURM
-
-The Intel MPI provides some useful variables that may be used in the scripts executed via the MPI.
-these include `PMI_RANK`,`PMI_SIZE` and `MPI_LOCALRANKID`.
-
-- The `PMI_RANK` and `MPI_LOCALRANKID` returns the process rank within the MPI_COMM_WORLD communicator - the process number
-- The `PMI_SIZE` returns the process rank within the MPI_COMM_WORLD communicator - the number of processes
-
-For example:
-
-```
-$ mpirun -n 4 /bin/bash -c 'echo $PMI_SIZE'
-4
-4
-4
-4
-```
-
-In typical multi-gpu multi-node setting using PyTorch one needs to know:
-
-- World-size - i.e. the total number of GPUs in the system
-- Rank of a job in the world - i.e. the number of the current GPU in the system
-- Local GPU ID for assignment purposes inside PyTorch/TF
-
-The following example assumes that you use PyTorch and your `DistributedDataParallel` process is being initialized via `init_method` pointing to some file.
-
-The required changes are:
-
-- To get the world size, access the `PMI_SIZE` variable of the MPI
-- To get the process rank in the world, access `PMI_RANK` variable of the MPI
-- To get local GPU ID on the node (can be used to manually set `CUDA_VISIBLE_DEVICES`), access the `MPI_LOCALRANKID` variable.
-
-!!! hint
-    Some jobs may greatly benefit from [mixed precision training][1] since the new NVIDIA A100 GPUs have excellent support for it.
-
-[1]: https://pytorch.org/docs/stable/amp.html
diff --git a/mkdocs.yml b/mkdocs.yml
index 6e82704ac6634855d094568b5f15998b9d836164..1f10b2e38c39a6c49b310b815335816d1cd83afb 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -110,7 +110,6 @@ nav:
         - HyperQueue: general/hyperqueue.md
       - Parallel Computing and MPI: general/karolina-mpi.md
       - Vnode Allocation: general/vnode-allocation.md
-      - Migrating from SLURM: general/slurmtopbs.md
     - Other Services:
         - OpenCode: general/opencode.md
     - Technical Information: