Submitting Jobs on HPC with SLURM

How to Effectively Work on JHPCE

Author

02-SLURM and the Cluster

Setup assumptions: You have SSH access to the cluster and R is available via modules or a system install. Replace partition/account names with your site’s values.

Warm‑up: Explore the cluster

Question. What partitions/queues can you use, and what’s the default time limit and CPU/memory policy?

Show solution

Code

# Partitions and key limits
sinfo -o '%P %l %c %m %a'   # Partition, time limit, CPUs, memory, availability

# Default Slurm config snippets
scontrol show config | egrep 'DefMemPerCPU|DefMemPerNode|SchedulerType|SelectType'

# Your account/QoS
sacctmgr show assoc user=$USER format=Cluster,Account,Partition,MaxWall,MaxCPUs,MaxJobs,Grp* -Pn 2>/dev/null || true

Notes: sinfo gives active partitions. scontrol show config reveals defaults like memory policy per CPU or per node.

Modules

Question. What modules are available? Which ones are loaded?

Code

module avail

HIPAA

Read the HIPAA section of https://jhpce.jhu.edu/joinus/hipaa/

SSH

Skim how to set up SSH: https://jhpce.jhu.edu/access/ssh/

Transfer one file

See https://jhpce.jhu.edu/access/file-transfer/ for transferring files, do this on the transfer node.

Get on the interactive node

Use --partition=interactive. Try to have 2 running.

Submit a minimal R job (single task)

Question. Write a Slurm batch script that runs a one‑liner in R and writes to slurm-%j.out. Name the job rmin and have a time limit of 5 minutes, with 2G of memory requested. The one line should just do cat("Hello from R on Slurm!\n")

Show solution

Code

cat > r_minimal.sbatch <<'SB'
#!/usr/bin/env bash
#SBATCH -J rmin
#SBATCH -t 00:05:00
#SBATCH -c 1
#SBATCH --mem=2G
#SBATCH -o slurm-%j.out

module load conda_R 2>/dev/null || true  # or: module load R; or skip if R in PATH
Rscript -e 'cat("Hello from R on Slurm!\n")'
SB

sbatch r_minimal.sbatch

%j expands to the JobID. Inspect output with tail -f slurm-<jobid>.out.

Parameterized simulation in R (script)

Question. Create sim.R that accepts command‑line args: n, mu, sigma, seed, runs a simple simulation (e.g., mean of rnorm), and writes a CSV line to results/sim_<seed>.csv. See ?commandArgs.

Show solution

Code

mkdir -p results

sim.R

Code

args <- commandArgs(trailingOnly = TRUE)
stopifnot(length(args) == 4)

n     <- as.integer(args[1])
mu    <- as.numeric(args[2])
sigma <- as.numeric(args[3])
seed  <- as.integer(args[4])

set.seed(seed)
x <- rnorm(n, mu, sigma)
res <- data.frame(n=n, mu=mu, sigma=sigma, seed=seed,
                  mean=mean(x), sd=sd(x))

out <- sprintf('results/sim_%d.csv', seed)
write.csv(res, out, row.names = FALSE)
cat('Wrote', out, '\n')

Batch script that passes parameters to R

Question. Write sim.sbatch that runs Rscript sim.R 10000 0 1 42.

Show solution

sim.sbatch

Code

#!/usr/bin/env bash
#SBATCH -J sim
#SBATCH -t 00:05:00
#SBATCH -c 1
#SBATCH --mem=2G
#SBATCH -o slurm-%j.out

module load conda_R 2>/dev/null || true
Rscript sim.R 10000 0 1 42

Code

sbatch sim.sbatch

Use `expand.grid` in R with `SLURM_ARRAY_TASK_ID` (no params.csv)

Question. Within R, generate a parameter grid and pick the row corresponding to your task index using SLURM_ARRAY_TASK_ID. Run sim.R with those values.

Show solution

driver.R:

Code

# Read the array index (default 1 when running locally)
idx <- as.integer(Sys.getenv('SLURM_ARRAY_TASK_ID', '1'))

# Define your parameter grid
params <- expand.grid(
  n    = c(1e4, 5e4),
  mu   = c(0, 0.2),
  sigma= c(1, 2),
  seed = 1:8
)

stopifnot(idx >= 1, idx <= nrow(params))
p <- params[idx, , drop = FALSE]

set.seed(p$seed)
x <- rnorm(n, mu, sigma)

driver_array.sbatch:

Code

#!/usr/bin/env bash
#SBATCH -J drv
#SBATCH -t 00:10:00
#SBATCH -c 1
#SBATCH --mem=2G
#SBATCH -o slurm-%A_%a.out
#SBATCH --array=1-64

# Minimal array submission (match the array range to nrow(params) = 64)
module load conda_R 2>/dev/null || true
Rscript driver.R

Code

sbatch driver_array.sbatch

Notes: - Ensure the array range matches nrow(params) inside driver.R. - Locally, you can test with SLURM_ARRAY_TASK_ID=3 Rscript driver.R.

Array job to run the grid

Question. Write sim_array.sbatch that runs one row of params.csv per array task and writes logs as slurm-%A_%a.out.

Show solution

sim_array.sbatch:

Code

#!/usr/bin/env bash
#SBATCH -J simarr
#SBATCH -t 00:10:00
#SBATCH -c 1
#SBATCH --mem=2G
#SBATCH -o slurm-%A_%a.out
#SBATCH --array=1-32           # <-- set to nrow(params.csv)

module load conda_R 2>/dev/null || true

# Read the line matching this array index
IFS=',' read -r n mu sigma seed < <(sed -n "${SLURM_ARRAY_TASK_ID}p" params.csv)

echo "Task ${SLURM_ARRAY_TASK_ID}: n=$n mu=$mu sigma=$sigma seed=$seed"
Rscript sim.R "$n" "$mu" "$sigma" "$seed"

Code

# Submit after matching the array range to your params
lines=$(wc -l < params.csv)
sbatch --array=1-$lines sim_array.sbatch

Key env vars: SLURM_ARRAY_TASK_ID (index), %A (ArrayJobID), %a (TaskID) for log naming.

Monitor, inspect, and cancel jobs

Question. How do you check running jobs and see finished job states? Cancel a stuck task 5 of an array.

Show solution

Code

# Running/queued jobs for you
squeue -u $USER -o '%A %j %t %M %D %R'

# Completed job accounting (after finish)
sacct -u $USER --starttime today \
  --format=JobID,JobName%30,State,Elapsed,MaxRSS,ExitCode

# Show details for a specific job
a_jobid=123456
scontrol show job $a_jobid | less

# Cancel a whole job or a single array task
scancel 123456           # whole job
scancel 123456_5         # only task 5

Use tail -f slurm-123456_5.out to live‑watch a specific task’s output.

Jobs with Dependencies

Read through https://hpc.nih.gov/docs/job_dependencies.html

Question. How can you run 2 jobs with the 2nd job depending on the first.

Resource requests & usage diagnostics

Question. Request 2 CPUs and 4G RAM per task; later, inspect actual usage.

Show solution

Code

# In your .sbatch header
#SBATCH -c 2
#SBATCH --mem=4G

# Inspect after completion
sacct -j 123456 -o JobID,JobName%30,AllocCPUS,Elapsed,MaxRSS,State,ExitCode

Tip: Prefer --mem= (per node) vs --mem-per-cpu= depending on your site policy.

Resubmit only failed array tasks

Question. Find which tasks failed from a previous array job and resubmit only those indices.

Show solution

Code

jid=123456  # parent array job ID
# List failed indices (State not COMPLETED)
fail=$(sacct -j $jid --format=JobID,State -n | awk -F'[_. ]' '$2!="batch" && $3!="COMPLETED" {print $2}' | sort -n | uniq)

echo "Failed indices: $fail"
[ -n "$fail" ] && sbatch --array=$(echo $fail | tr ' ' ',') sim_array.sbatch

This parses sub‑job entries like 123456_7 and extracts 7 when State != COMPLETED.

Interactive work (debugging)

Question. Start an interactive shell on a compute node and verify R sees multiple threads.

Show solution

Code

# Allocate and attach to a compute node for 10 min with 2 CPUs and 2G RAM
salloc -t 00:10:00 -c 2 --mem=2G
srun --pty bash

module load conda_R 2>/dev/null || true
R -q <<'RS'
parallel::detectCores()
sessionInfo()
RS

# Exit when done
exit  # from R
exit  # from shell to release allocation

VS Code / Positron remote dev

Question. Configure VS Code (or Positron) to edit/submit jobs on the cluster via SSH.

Show solution

VS Code (Remote - SSH):

Install extensions: Remote - SSH, R, optionally Python, Bash IDE.

Create ~/.ssh/config entry on your laptop:

Host myhpc
  HostName login.cluster.edu
  User your_netid
  IdentityFile ~/.ssh/id_ed25519

In VS Code: Remote Explorer → SSH Targets → myhpc → Connect.
Open your home/project directory on the cluster.
Ensure R is available in PATH on the cluster; set VS Code R extension (if needed) to use /usr/bin/R or your module path.
Use VS Code terminal (connected to myhpc) to run sbatch, squeue, etc. Edit .sbatch/.R files locally but they execute on the cluster.

Positron:

Install the Remote - SSH (or built‑in remote) capability; connect similarly to open a remote workspace.
Configure the R path in Positron settings to point to the cluster’s R binary; use the integrated terminal for sbatch.

Optional: set up SSH keys and agent forwarding to enable Git from the cluster.

Helpful shell aliases/functions for SLURM

Task: Look over these and add helpers to your ~/.bash_profile to speed up common tasks. Better yet, make a ~/.bash_aliases and put this in ~/.bashrc:

Code

# User specific aliases and functions
if [ -f ~/.bash_aliases ]; then
    . ~/.bash_aliases
fi

Commands:

Code

cat >> ~/.bashrc <<'BRC'
# Slurm quick views
alias sj='squeue -u $USER -o "%A %j %t %M %D %R"'
alias sa='sacct -u $USER --starttime today -o JobID,JobName%30,State,Elapsed,MaxRSS,ExitCode'

# Tail latest log(s)
sl(){ tail -n +1 -f slurm-*.out; }

# Submit and print JobID only
sb(){ sbatch --parsable "$@"; }

# Describe a job
sd(){ scontrol show job "$1" | less; }

# Resubmit failed array tasks for a parent JobID
sref(){ jid="$1"; idx=$(sacct -j "$jid" -n -o JobID,State | awk -F'[_. ]' '$2!="batch" && $3!="COMPLETED"{print $2}' | sort -n | uniq | paste -sd, -); [ -n "$idx" ] && sbatch --array="$idx" sim_array.sbatch; }

alias sqme="squeue --me"

Rnosave () 
{ 
    x="$1";
    tempfile=`mktemp file.XXXX.sh`;
    echo "#!/bin/bash" > $tempfile;
    echo ". ~/.bash_profile" >> $tempfile;
    echo "R --no-save < ${x}" >> $tempfile;
    shift;
    cmd="${submitter} $@ $tempfile";
    echo "cmd is $cmd";
    ${cmd};
    rm $tempfile
}

## Git Add, Commit, Push (GACP)
function gacp { 
    git pull;
    git add --all .;
    git commit -m "${1}";
    if [ -n "${2}" ]; then
        echo "Tagging Commit";
        git tag "${2}";
        git push origin "${2}";
        git commit --amend -m "${1} [ci skip]";
    fi;
    git push origin
}

## raw ls
alias rls="/usr/bin/ls -f"

## grep on history this is really important
function hgrep {
    history | grep "$@"
}

BRC

# Reload shell config
source ~/.bashrc

These helpers give you one‑letter shortcuts for listing jobs (sj), recent accounting (sa), tailing logs (sl), describing a job (sd), and resubmitting failures (sref).

Bonus: Make a project scaffold

Question. Create a scaffold with directories and template scripts for simulations.

Show solution

Code

mkdir -p {scripts,results,logs}

# Template sbatch header you can copy into scripts/
cat > scripts/_header.sbatch <<'H'
#!/usr/bin/env bash
#SBATCH -t 00:10:00
#SBATCH -c 1
#SBATCH --mem=2G
#SBATCH -o logs/slurm-%A_%a.out
H

Now copy _header.sbatch into new jobs and append your commands.

Deliverables (for practice)

r_minimal.sbatch and output log
sim.R, params.csv, sim_array.sbatch
Evidence of a dependency submission (combine.sbatch and combined output)
Your updated ~/.bashrc helpers

--- title: "Submitting Jobs on HPC with SLURM" subtitle: "How to Effectively Work on JHPCE" author: "02-SLURM and the Cluster" format: html: toc: true code-fold: true code-tools: true editor: source engine: knitr --- > **Setup assumptions:** You have SSH access to the cluster and R is available via modules or a system install. Replace partition/account names with your site's values. ------------------------------------------------------------------------ ## Warm‑up: Explore the cluster **Question.** What partitions/queues can you use, and what's the default time limit and CPU/memory policy? <details> <summary>Show solution</summary> ```{bash, eval = FALSE} # Partitions and key limits sinfo -o '%P %l %c %m %a' # Partition, time limit, CPUs, memory, availability # Default Slurm config snippets scontrol show config | egrep 'DefMemPerCPU|DefMemPerNode|SchedulerType|SelectType' # Your account/QoS sacctmgr show assoc user=$USER format=Cluster,Account,Partition,MaxWall,MaxCPUs,MaxJobs,Grp* -Pn 2>/dev/null || true ``` Notes: `sinfo` gives active partitions. `scontrol show config` reveals defaults like memory policy per CPU or per node. </details> ------------------------------------------------------------------------ ### Modules **Question.** What modules are available? Which ones are loaded? ```{bash, eval = FALSE} module avail ``` ### HIPAA Read the HIPAA section of [https://jhpce.jhu.edu/joinus/hipaa/](https://jhpce.jhu.edu/joinus/hipaa/) ### SSH Skim how to set up SSH: [https://jhpce.jhu.edu/access/ssh/](https://jhpce.jhu.edu/access/ssh/) ### Transfer one file See [https://jhpce.jhu.edu/access/file-transfer/](https://jhpce.jhu.edu/access/file-transfer/) for transferring files, do this on the transfer node. ### Get on the interactive node Use `--partition=interactive`. Try to have 2 running. ------------------------------------------------------------------------ ## Submit a minimal R job (single task) **Question.** Write a Slurm batch script that runs a one‑liner in R and writes to `slurm-%j.out`. Name the job `rmin` and have a time limit of 5 minutes, with 2G of memory requested. The one line should just do `cat("Hello from R on Slurm!\n")` <details> <summary>Show solution</summary> ```{bash, eval = FALSE} cat > r_minimal.sbatch <<'SB' #!/usr/bin/env bash #SBATCH -J rmin #SBATCH -t 00:05:00 #SBATCH -c 1 #SBATCH --mem=2G #SBATCH -o slurm-%j.out module load conda_R 2>/dev/null || true # or: module load R; or skip if R in PATH Rscript -e 'cat("Hello from R on Slurm!\n")' SB sbatch r_minimal.sbatch ``` `%j` expands to the JobID. Inspect output with `tail -f slurm-<jobid>.out`. </details> ------------------------------------------------------------------------ ## Parameterized simulation in R (script) **Question.** Create `sim.R` that accepts command‑line args: `n`, `mu`, `sigma`, `seed`, runs a simple simulation (e.g., mean of `rnorm`), and writes a CSV line to `results/sim_<seed>.csv`. See `?commandArgs`. <details> <summary>Show solution</summary> ```{bash, eval = FALSE} mkdir -p results ``` `sim.R` ```{r, eval = FALSE} args <- commandArgs(trailingOnly = TRUE) stopifnot(length(args) == 4) n <- as.integer(args[1]) mu <- as.numeric(args[2]) sigma <- as.numeric(args[3]) seed <- as.integer(args[4]) set.seed(seed) x <- rnorm(n, mu, sigma) res <- data.frame(n=n, mu=mu, sigma=sigma, seed=seed, mean=mean(x), sd=sd(x)) out <- sprintf('results/sim_%d.csv', seed) write.csv(res, out, row.names = FALSE) cat('Wrote', out, '\n') ``` </details> ------------------------------------------------------------------------ ## Batch script that passes parameters to R **Question.** Write `sim.sbatch` that runs `Rscript sim.R 10000 0 1 42`. <details> <summary>Show solution</summary> `sim.sbatch` ```{bash, eval = FALSE} #!/usr/bin/env bash #SBATCH -J sim #SBATCH -t 00:05:00 #SBATCH -c 1 #SBATCH --mem=2G #SBATCH -o slurm-%j.out module load conda_R 2>/dev/null || true Rscript sim.R 10000 0 1 42 ``` ```{bash, eval = FALSE} sbatch sim.sbatch ``` </details> ------------------------------------------------------------------------ ## Use `expand.grid` in R with `SLURM_ARRAY_TASK_ID` (no params.csv) **Question.** Within R, generate a parameter grid and pick the row corresponding to your task index using `SLURM_ARRAY_TASK_ID`. Run `sim.R` with those values. <details><summary>Show solution</summary> `driver.R`: ```{r, eval = FALSE} # Read the array index (default 1 when running locally) idx <- as.integer(Sys.getenv('SLURM_ARRAY_TASK_ID', '1')) # Define your parameter grid params <- expand.grid( n = c(1e4, 5e4), mu = c(0, 0.2), sigma= c(1, 2), seed = 1:8 ) stopifnot(idx >= 1, idx <= nrow(params)) p <- params[idx, , drop = FALSE] set.seed(p$seed) x <- rnorm(n, mu, sigma) ``` `driver_array.sbatch`: ```{bash, eval = FALSE} #!/usr/bin/env bash #SBATCH -J drv #SBATCH -t 00:10:00 #SBATCH -c 1 #SBATCH --mem=2G #SBATCH -o slurm-%A_%a.out #SBATCH --array=1-64 # Minimal array submission (match the array range to nrow(params) = 64) module load conda_R 2>/dev/null || true Rscript driver.R ``` ```{bash, eval = FALSE} sbatch driver_array.sbatch ``` Notes: - Ensure the array range matches `nrow(params)` inside `driver.R`. - Locally, you can test with `SLURM_ARRAY_TASK_ID=3 Rscript driver.R`. </details> ------------------------------------------------------------------------ ## Array job to run the grid **Question.** Write `sim_array.sbatch` that runs one row of `params.csv` per array task and writes logs as `slurm-%A_%a.out`. <details> <summary>Show solution</summary> `sim_array.sbatch`: ```{bash, eval = FALSE} #!/usr/bin/env bash #SBATCH -J simarr #SBATCH -t 00:10:00 #SBATCH -c 1 #SBATCH --mem=2G #SBATCH -o slurm-%A_%a.out #SBATCH --array=1-32 # <-- set to nrow(params.csv) module load conda_R 2>/dev/null || true # Read the line matching this array index IFS=',' read -r n mu sigma seed < <(sed -n "${SLURM_ARRAY_TASK_ID}p" params.csv) echo "Task ${SLURM_ARRAY_TASK_ID}: n=$n mu=$mu sigma=$sigma seed=$seed" Rscript sim.R "$n" "$mu" "$sigma" "$seed" ``` ```{bash, eval = FALSE} # Submit after matching the array range to your params lines=$(wc -l < params.csv) sbatch --array=1-$lines sim_array.sbatch ``` Key env vars: `SLURM_ARRAY_TASK_ID` (index), `%A` (ArrayJobID), `%a` (TaskID) for log naming. </details> ------------------------------------------------------------------------ ## Monitor, inspect, and cancel jobs **Question.** How do you check running jobs and see finished job states? Cancel a stuck task 5 of an array. <details> <summary>Show solution</summary> ```{bash, eval = FALSE} # Running/queued jobs for you squeue -u $USER -o '%A %j %t %M %D %R' # Completed job accounting (after finish) sacct -u $USER --starttime today \ --format=JobID,JobName%30,State,Elapsed,MaxRSS,ExitCode # Show details for a specific job a_jobid=123456 scontrol show job $a_jobid | less # Cancel a whole job or a single array task scancel 123456 # whole job scancel 123456_5 # only task 5 ``` Use `tail -f slurm-123456_5.out` to live‑watch a specific task's output. </details> ------------------------------------------------------------------------ ## Jobs with Dependencies Read through [https://hpc.nih.gov/docs/job_dependencies.html](https://hpc.nih.gov/docs/job_dependencies.html) **Question.** How can you run 2 jobs with the 2nd job depending on the first. ------------------------------------------------------------------------ ## Resource requests & usage diagnostics **Question.** Request 2 CPUs and 4G RAM per task; later, inspect actual usage. <details> <summary>Show solution</summary> ```{bash, eval = FALSE} # In your .sbatch header #SBATCH -c 2 #SBATCH --mem=4G # Inspect after completion sacct -j 123456 -o JobID,JobName%30,AllocCPUS,Elapsed,MaxRSS,State,ExitCode ``` Tip: Prefer `--mem=` (per node) vs `--mem-per-cpu=` depending on your site policy. </details> ------------------------------------------------------------------------ ## Resubmit only failed array tasks **Question.** Find which tasks failed from a previous array job and resubmit only those indices. <details> <summary>Show solution</summary> ```{bash, eval = FALSE} jid=123456 # parent array job ID # List failed indices (State not COMPLETED) fail=$(sacct -j $jid --format=JobID,State -n | awk -F'[_. ]' '$2!="batch" && $3!="COMPLETED" {print $2}' | sort -n | uniq) echo "Failed indices: $fail" [ -n "$fail" ] && sbatch --array=$(echo $fail | tr ' ' ',') sim_array.sbatch ``` This parses sub‑job entries like `123456_7` and extracts `7` when `State != COMPLETED`. </details> ------------------------------------------------------------------------ ## Interactive work (debugging) **Question.** Start an interactive shell on a compute node and verify R sees multiple threads. <details> <summary>Show solution</summary> ```{bash, eval = FALSE} # Allocate and attach to a compute node for 10 min with 2 CPUs and 2G RAM salloc -t 00:10:00 -c 2 --mem=2G srun --pty bash module load conda_R 2>/dev/null || true R -q <<'RS' parallel::detectCores() sessionInfo() RS # Exit when done exit # from R exit # from shell to release allocation ``` </details> ------------------------------------------------------------------------ ## VS Code / Positron remote dev **Question.** Configure VS Code (or Positron) to edit/submit jobs on the cluster via SSH. <details> <summary>Show solution</summary> **VS Code (Remote - SSH):** 1. Install extensions: *Remote - SSH*, *R*, optionally *Python*, *Bash IDE*. 2. Create `~/.ssh/config` entry on your laptop: ``` Host myhpc HostName login.cluster.edu User your_netid IdentityFile ~/.ssh/id_ed25519 ``` 3. In VS Code: *Remote Explorer → SSH Targets → myhpc → Connect*. 4. Open your home/project directory on the cluster. 5. Ensure R is available in PATH on the cluster; set VS Code R extension (if needed) to use `/usr/bin/R` or your module path. 6. Use VS Code terminal (connected to myhpc) to run `sbatch`, `squeue`, etc. Edit `.sbatch`/`.R` files locally but they execute on the cluster. **Positron:** - Install the *Remote - SSH* (or built‑in remote) capability; connect similarly to open a remote workspace. - Configure the R path in Positron settings to point to the cluster's R binary; use the integrated terminal for `sbatch`. **Optional:** set up SSH keys and agent forwarding to enable Git from the cluster. </details> ------------------------------------------------------------------------ ## Helpful shell aliases/functions for SLURM **Task**: Look over these and add helpers to your `~/.bash_profile` to speed up common tasks. Better yet, make a `~/.bash_aliases` and put this in `~/.bashrc`: ```{bash, eval = FALSE} # User specific aliases and functions if [ -f ~/.bash_aliases ]; then . ~/.bash_aliases fi ``` Commands: ```{bash, eval = FALSE} cat >> ~/.bashrc <<'BRC' # Slurm quick views alias sj='squeue -u $USER -o "%A %j %t %M %D %R"' alias sa='sacct -u $USER --starttime today -o JobID,JobName%30,State,Elapsed,MaxRSS,ExitCode' # Tail latest log(s) sl(){ tail -n +1 -f slurm-*.out; } # Submit and print JobID only sb(){ sbatch --parsable "$@"; } # Describe a job sd(){ scontrol show job "$1" | less; } # Resubmit failed array tasks for a parent JobID sref(){ jid="$1"; idx=$(sacct -j "$jid" -n -o JobID,State | awk -F'[_. ]' '$2!="batch" && $3!="COMPLETED"{print $2}' | sort -n | uniq | paste -sd, -); [ -n "$idx" ] && sbatch --array="$idx" sim_array.sbatch; } alias sqme="squeue --me" Rnosave () { x="$1"; tempfile=`mktemp file.XXXX.sh`; echo "#!/bin/bash" > $tempfile; echo ". ~/.bash_profile" >> $tempfile; echo "R --no-save < ${x}" >> $tempfile; shift; cmd="${submitter} $@ $tempfile"; echo "cmd is $cmd"; ${cmd}; rm $tempfile } ## Git Add, Commit, Push (GACP) function gacp { git pull; git add --all .; git commit -m "${1}"; if [ -n "${2}" ]; then echo "Tagging Commit"; git tag "${2}"; git push origin "${2}"; git commit --amend -m "${1} [ci skip]"; fi; git push origin } ## raw ls alias rls="/usr/bin/ls -f" ## grep on history this is really important function hgrep { history | grep "$@" } BRC # Reload shell config source ~/.bashrc ``` These helpers give you one‑letter shortcuts for listing jobs (`sj`), recent accounting (`sa`), tailing logs (`sl`), describing a job (`sd`), and resubmitting failures (`sref`). ------------------------------------------------------------------------ ## Bonus: Make a project scaffold **Question.** Create a scaffold with directories and template scripts for simulations. <details> <summary>Show solution</summary> ```{bash, eval = FALSE} mkdir -p {scripts,results,logs} # Template sbatch header you can copy into scripts/ cat > scripts/_header.sbatch <<'H' #!/usr/bin/env bash #SBATCH -t 00:10:00 #SBATCH -c 1 #SBATCH --mem=2G #SBATCH -o logs/slurm-%A_%a.out H ``` Now copy `_header.sbatch` into new jobs and append your commands. </details> ------------------------------------------------------------------------ ## Deliverables (for practice) - `r_minimal.sbatch` and output log - `sim.R`, `params.csv`, `sim_array.sbatch` - Evidence of a dependency submission (`combine.sbatch` and combined output) - Your updated `~/.bashrc` helpers

Warm‑up: Explore the cluster

Modules

HIPAA

SSH

Transfer one file

Get on the interactive node

Submit a minimal R job (single task)

Parameterized simulation in R (script)

Batch script that passes parameters to R

Use expand.grid in R with SLURM_ARRAY_TASK_ID (no params.csv)

Array job to run the grid

Monitor, inspect, and cancel jobs

Jobs with Dependencies

Resource requests & usage diagnostics

Resubmit only failed array tasks

Interactive work (debugging)

VS Code / Positron remote dev

Helpful shell aliases/functions for SLURM

Bonus: Make a project scaffold

Deliverables (for practice)

Use `expand.grid` in R with `SLURM_ARRAY_TASK_ID` (no params.csv)