Add Schedd plugin to synch with CC.

This should be much more reliable, albeit being more prone to crash a HTCondor component (the schedd) if there's a bug...

ReadMe.md

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+# HTCondor to ClusterCockpit Sync
+## HTCondor ClassAdLog Plugin
+
+### Building
+Requirements:
+A build environment reasonably similar to the submission nodes (might want to use the HTCondor nmi build docker containers).
+
+Use CMake to configure the project.
+```bash
+mkdir build ; cd build
+cmake .. -DCONDOR_SRC=<path/to/htcondor> -DCONDOR_BUILD=<path/to/htcondor/build> -DCMAKE_BUILD_TYPE=Release
+```
+
+### Configuration
+The target system will need the corresponding `curl` package installed.
+
+Adapt and add to `condor_config.local` or any other HTCondor config file:
+```
+SCHEDD.PLUGINS = $(SCHEDD.PLUGINS) /path/to/libhtcondor_cc_sync_plugin.so
+
+CCSYNC_URL=<ClusterCockpit-URL>
+CCSYNC_APIKEY=<API-Key>
+CCSYNC_CLUSTER_NAME=<ClusterCockpit's cluster name this submit node works for>
+CCSYNC_GPU_MAP=/path/to/gpu_map.json
+CCSYNC_SUBMIT_ID=<Unique submission node id, expected to be in 0..3 (see #globalJobIdToInt)>
+```
+
+`gpu_map.json` is expected in the format and can be generated with `condor_status_to_gpu_map.py <path/to/condor_status.json>`, where `condor_status.json` is generated by calling `condor_status -json > condor_status.json` on the cluster:
+```
+{
+    "hostname1": {
+        "GPU-acb66c44": "0000:07:00.0",
+        ...
+    },
+    "hostname2": {
+        "GPU-31f57da0": "0000:0A:00.0",
+        ...
+    }
+}
+```