deploy: ce57072

hpc-tutorial/episode-0/index.html

@@ -3251,9 +3251,9 @@ <h2 id="legend">Legend<a class="headerlink" href="#legend" title="Permanent link
 <p>While file paths are highlighted like this: <code>/data/cephfs-1/work/projects/cubit/current</code>.</p>
 <h2 id="instant-gratification">Instant Gratification<a class="headerlink" href="#instant-gratification" title="Permanent link">&para;</a></h2>
 <p>After connecting to the cluster, you are located on a login node.
-To get to your first compute node, type <code>srun --time 7-00 --mem=8G --ntasks=8 --pty bash -i</code> which will launch an interactive Bash session on a free remote node running up to 7 days, enabling you to use 8 cores and 8 Gb memory. Typing <code>exit</code> will you bring back to the login node.</p>
-<div class="highlight"><pre><span></span><code>$ srun -p long --time 7-00 --mem=8G --ntasks=8 --pty bash -i
-med0107 $ exit
+To get to your first compute node, type <code>srun --time 7-00 --mem=8G --cpus-per-task=8 --pty bash -i</code> which will launch an interactive Bash session on a free remote node running up to 7 days, enabling you to use 8 cores and 8 Gb memory. Typing <code>exit</code> will you bring back to the login node.</p>
+<div class="highlight"><pre><span></span><code>hpc-login-1$ srun -p long --time 7-00 --mem=8G --cpus-per-task=8 --pty bash -i
+hpc-cpu-1$ exit
 $
 </code></pre></div>
 <p>See?
@@ -3263,7 +3263,7 @@ <h2 id="preparation">Preparation<a class="headerlink" href="#preparation" title=
 In general the users on the cluster will manage their own software with the help of conda.
 If you haven't done so so far, please <a href="../../best-practice/software-installation-with-conda/">follow the instructions in installing conda</a> first.
 The only premise is that you are able to <a href="../../connecting/advanced-ssh/linux/">log into the cluster</a>.
-Make also sure that you are logged in to a computation node using <code>srun -p medium --time 1-00 --mem=4G --ntasks=1 --pty bash -i</code>.</p>
+Make also sure that you are logged in to a computation node using <code>srun -p medium --time 1-00 --mem=4G --cpus-per-task=1 --pty bash -i</code>.</p>
 <p>Now we will create a new environment, so as to not interfere
 with your current or planned software stack, and install into it all the
 software that we need during the tutorial. Run the following commands:</p>

hpc-tutorial/episode-1/index.html

@@ -3315,7 +3315,7 @@ <h1 id="first-steps-episode-1">First Steps: Episode 1<a class="headerlink" href=
 Here we will build a small pipeline with alignment and variant calling.
 The premise is that you have the tools installed as described in <a href="../episode-0/">Episode 0</a>. For this episode, please make sure that you
 are on a compute node. As a reminder, the command to access a compute node with the required resources is</p>
-<div class="highlight"><pre><span></span><code>$ srun --time 7-00 --mem=8G --ntasks=8 --pty bash -i
+<div class="highlight"><pre><span></span><code>$ srun --time 7-00 --mem=8G --cpus-per-task=8 --pty bash -i
 </code></pre></div>
 <h2 id="tutorial-input-files">Tutorial Input Files<a class="headerlink" href="#tutorial-input-files" title="Permanent link">&para;</a></h2>
 <p>We will provide you with some example FASTQ files, but you can use your own if you like.

hpc-tutorial/episode-2/index.html

@@ -3250,8 +3250,8 @@ <h2 id="the-sbatch-command">The <code>sbatch</code> Command<a class="headerlink"
 <span class="c1"># Set the file to write the stdout and stderr to (if -e is not set; -o or --output).</span>
 <span class="c1">#SBATCH --output=logs/%x-%j.log</span>
 
-<span class="c1"># Set the number of cores (-n or --ntasks).</span>
-<span class="c1">#SBATCH --ntasks=8</span>
+<span class="c1"># Set the number of cores (-c or --cpus-per-task).</span>
+<span class="c1">#SBATCH --cpus-per-task=8</span>
 
 <span class="c1"># Force allocation of the two cores on ONE node.</span>
 <span class="c1">#SBATCH --nodes=1</span>
@@ -3293,8 +3293,8 @@ <h2 id="the-sbatch-command">The <code>sbatch</code> Command<a class="headerlink"
 <span class="c1"># Set the file to write the stdout and stderr to (if -e is not set; -o or --output).</span>
 <span class="c1">#SBATCH --output=logs/%x-%j.log</span>
 
-<span class="c1"># Set the number of cores (-n or --ntasks).</span>
-<span class="c1">#SBATCH --ntasks=8</span>
+<span class="c1"># Set the number of cores (-c or --cpus-per-task).</span>
+<span class="c1">#SBATCH --cpus-per-task=8</span>
 
 <span class="c1"># Force allocation of the two cores on ONE node.</span>
 <span class="c1">#SBATCH --nodes=1</span>

hpc-tutorial/episode-4/index.html

@@ -3154,8 +3154,8 @@ <h1 id="first-steps-episode-4">First Steps: Episode 4<a class="headerlink" href=
 <span class="c1"># Set the file to write the stdout and stderr to (if -e is not set; -o or --output).</span>
 <span class="c1">#SBATCH --output=logs/%x-%j.log</span>
 
-<span class="c1"># Set the number of cores (-n or --ntasks).</span>
-<span class="c1">#SBATCH --ntasks=2</span>
+<span class="c1"># Set the number of cores (-c or --cpus-per-task).</span>
+<span class="c1">#SBATCH --cpus-per-task=2</span>
 
 <span class="c1"># Force allocation of the two cores on ONE node.</span>
 <span class="c1">#SBATCH --nodes=1</span>

slurm/commands-sbatch/index.html

@@ -3253,8 +3253,8 @@ <h2 id="important-arguments">Important Arguments<a class="headerlink" href="#imp
     This is only given here as an important argument as the maximum number of nodes allocatable to any partition but <code>mpi</code> is set to one (1).
     This is done as there are few users on the BIH HPC that actually use multi-node paralleilsm.
     Rather, most users will use multi-core parallelism and might forget to limit the number of nodes which causes inefficient allocation of resources.</li>
-<li><code>--ntasks</code>
-    -- This corresponds to the number of threads allocated to each node.</li>
+<li><code>--cpus-per-task</code>
+    -- This corresponds to the number of CPU cores allocated to each task.</li>
 <li><code>--mem</code>
     -- The memory to allocate for the job.
     As you can define minimal and maximal number of tasks/CPUs/cores, you could also specify <code>--mem-per-cpu</code> and get more flexible scheduling of your job.</li>