Testing the username filter

merlin6-test/cluster_info.json

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+{
+    "name" : "merlin6-test",
+    "worker_bin_path" : "/data/user/USERNAME/cryosparc/cryosparc2_worker/bin/cryosparcw",
+    "cache_path" : "/scratch/",
+    "send_cmd_tpl" : "{{ command }}",
+    "qsub_cmd_tpl" : "sbatch {{ script_path_abs }}",
+    "qstat_cmd_tpl" : "squeue -j {{ cluster_job_id }}",
+    "qdel_cmd_tpl" : "scancel {{ cluster_job_id }}",
+    "qinfo_cmd_tpl" : "sinfo",
+    "transfer_cmd_tpl" : "cp {{ src_path }} {{ dest_path }}"
+}

merlin6-test/cluster_script.sh

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+#!/usr/bin/env bash
+# cryoSPARC cluster submission script template for SLURM
+# Lane: merlin6-test v1.2.1 (2020-03-27)
+#
+# If you edit this file, run 'cryosparcm cluster connect'
+
+{# This template uses jinja2 syntax. #}
+{%- macro _min(a, b) -%}
+  {%- if a <= b %}{{a}}{% else %}{{b}}{% endif -%}
+{%- endmacro -%}
+
+# Available variables:
+#  script_path_abs={{ script_path_abs }}
+#      - the absolute path to the generated submission script
+#  run_cmd={{ run_cmd }}
+#      - the complete command-line string to run the job
+#  num_cpu={{ num_cpu }}
+#      - the number of CPUs needed
+#  num_gpu={{ num_gpu }}
+#      - the number of GPUs needed. Note: the code will use this many GPUs
+#        starting from dev id 0. The cluster scheduler or this script have the
+#        responsibility of setting CUDA_VISIBLE_DEVICES so that the job code
+#        ends up using the correct cluster-allocated GPUs.
+#  ram_gb={{ ram_gb }}
+#      - the amount of RAM needed in GB
+#  job_dir_abs={{ job_dir_abs }}
+#      - absolute path to the job directory
+#  project_dir_abs={{ project_dir_abs }}
+#      - absolute path to the project dir
+#  job_log_path_abs={{ job_log_path_abs }}
+#      - absolute path to the log file for the job
+#  worker_bin_path={{ worker_bin_path }}
+#      - absolute path to the cryosparc worker command
+#  run_args={{ run_args }}
+#      - arguments to be passed to cryosparcw run
+#  project_uid={{ project_uid }}
+#      - uid of the project
+#  job_uid={{ job_uid }}
+#      - uid of the job
+#  job_creator={{ job_creator }}
+#      - name of the user that created the job (may contain spaces)
+#  cryosparc_username={{ cryosparc_username }}
+#      - cryosparc username of the user that created the job (usually an email)
+
+#SBATCH --job-name=cryosparc_{{ project_uid }}_{{ job_uid }}
+#SBATCH --output={{ job_log_path_abs }}.out
+#SBATCH --error={{ job_log_path_abs }}.err
+#SBATCH --ntasks=1
+#SBATCH --threads-per-core=1
+#SBATCH --mem-per-cpu={{ ((ram_gb*1000)/num_cpu)|int }}M
+#SBATCH --time=0-01:00:00
+
+{%- if num_gpu == 0 %}
+# Use CPU cluster
+#SBATCH --partition=general
+#SBATCH --account=merlin
+#SBATCH --cpus-per-task={{ num_cpu }}
+{%- else %}
+# Use GPU cluster
+#SBATCH --partition=gpu-test
+#SBATCH --account=merlin-gpu
+#SBATCH --gres=gpu:GTX1080:{{ _min(num_gpu, 4) }}
+  {%- if num_gpu <= 2 %}
+#SBATCH --cpus-per-task={{ _min(num_cpu, 8) }}
+  {%- else %}
+    {# Slurm requests too many CPU sometimes; restrict to 20 per machine #}
+    {%- set num_nodes = (num_gpu/4) | round(0, 'ceil') | int %}
+#SBATCH --cpus-per-task={{ _min(num_cpu, 20*num_nodes) }}
+  {%- endif %}
+{%- endif %}
+
+# Print hostname, for debugging
+hostname
+
+# Make sure this matches the version of cuda used to compile cryosparc
+module purge
+module load cuda/10.0.130
+
+srun {{ run_cmd }}