See what your HPC compute really cost — in dollars, energy, and burgers.
A zero-dependency terminal tool that reads your Slurm job history via sacct
and generates an interactive receipt showing compute charges, energy usage,
AWS cost equivalents, and fun real-world conversions. It also roasts you
about your failed jobs with data-backed commentary.
====================================================
_[==]_
|o o|
|______|
The General Store
====================================================
Customer: you
Period: 2026-03-25 -> 2026-04-07 20:24
Days: 14
----------------------------------------------------
ORDER SUMMARY
----------------------------------------------------
Jobs submitted .......................... 26,189
Completed ............................ 26,085
Failed ....................................57
Cancelled .................................21
Timed out ..................................3
Success: [##########################..] 100%
# From PyPI (recommended)
pip install slurm-receipt
# Or with pipx (isolated install)
pipx install slurm-receipt
# Or from source
git clone https://github.com/chen-hsieh/slurm-receipt.git
cd slurm-receipt
pip install -e .Requirements: Python 3.8+, access to sacct (any Slurm cluster), a
terminal with curses support. Zero external Python dependencies.
# Interactive receipt for the last 30 days
slurm-receipt
# Last 90 days
slurm-receipt --days 90
# Custom date range
slurm-receipt --start 2025-01-01 --end 2025-12-31
# Plain text output (no TUI)
slurm-receipt --snap
# Save to a specific file
slurm-receipt --snap-file my_receipt.txt
# Try it without a Slurm cluster (synthetic data)
slurm-receipt --demo
# Add UGA Bulldogs flavor to roasts
slurm-receipt --ugaThe receipt shows your compute charges like a store receipt:
----------------------------------------------------
COMPUTE CHARGES
----------------------------------------------------
CPU time ........................ 18,597 core-hrs
Wall time ......................... 1,008 hrs
Memory ........................ 176,483 GB-hrs
Energy (CPU) ..................... 148.78 kWh
Cooling overhead ......................... x1.3
------------------------------------------------
TOTAL ENERGY ..................... 193.41 kWh
CO2 emitted ...................... 77.37 kg
----------------------------------------------------
AWS PRICE CHECK (on-demand)
----------------------------------------------------
Compute (CPU) ........................ $929.87
Memory ............................... $882.41
------------------------------------------------
TOTAL ............................ $1,812.28
****************************************************
BUT ACTUALLY...
****************************************************
~B~ 276.3
burgers grilled
"Enough to run a food truck for a day"
[1/37] (food)
Press h to see your submission patterns — weekly volume, day-of-week,
and time-of-day breakdowns:
WEEKLY BREAKDOWN
------------------------------------------------
Mar 25-31 [####################] 25971 <-
Apr 01-07 [#.....................] 218
DAY OF WEEK
------------------------------------------------
Monday [#####.............] 43
Tuesday [##################] 63 <-
Wednesday [##############....] 55
Thursday [#.................] 4
Friday [###########.......] 40
Saturday [############......] 25946 <-
Sunday [###...............] 25
TIME OF DAY
------------------------------------------------
12am-4am [....................] 0
4am-8am [....................] 0
8am-12pm [####................] 2593
12pm-4pm [####################] 10382
4pm-8pm [################....] 7786
8pm-12am [###########.........] 5428
Press r to see data-driven roasts with a mini receipt showing the
referenced job info:
25,963 jobs on 2026-03-28.
That's one every 3s.
Were you okay?
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
| RELATED JOB INFO |
|----------------------------------------------|
| Detail: 25,963 jobs on 2026-03-28 |
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
[1/6]
Press t to see your hungriest jobs by CPU-hours, plus the failure
hall of shame:
TOP 10 HUNGRIEST JOBS
====================================================
# Job Name CPU-hrs
------------------------------------------------
1. genera_717hap1 9,216
2. genera_717hap2 8,832
3. build_diamond_nr 768
4. syn_ks 36
...
| Key | Action |
|---|---|
< / > |
Rotate through 37 fun conversions |
r |
Performance review (roasts) |
m |
Monthly ledger |
h |
Activity report (weekly/daily/hourly) |
t |
Top jobs + failure hall of shame |
s |
Save receipt to ~/slurm_receipt_30d.txt + copy to clipboard |
j/k or arrows |
Scroll |
PgUp/PgDn |
Scroll fast |
b |
Back to main receipt |
q |
Quit (prints save location) |
Mouse scroll and status bar clicks also work in supported terminals.
| Metric | Method | Source |
|---|---|---|
| CPU energy | core-hours x 8W per core / 1000 | Blended avg across HPC nodes |
| GPU energy | GPU-hours x GPU TDP / 1000 | A100=400W, H100=700W, L4=72W, etc. |
| Cooling overhead | Total energy x 1.3 PUE | Industry standard data center PUE |
| CO2 emissions | kWh x 0.4 kg/kWh | US Southeast electricity grid |
| AWS cost | On-demand list prices, US regions | 2026 pricing |
Rotate through with </>:
- Food: burgers, cakes, ramen, espresso, toast, pizza, popcorn, rice
- Energy: phone charges, laptop charges, AA batteries, lightning bolts
- Transport: Tesla miles, e-bike miles, transatlantic flights
- Household: laundry loads, showers, houses powered, fridge days
- Entertainment: Netflix hours, gaming hours, vinyl albums
- Scale: ISS orbits, Bitcoin transactions, ChatGPT queries, MRI scans
- Memory: novels in RAM, photos, human genomes, full Wikipedias
- Environment: trees to offset, CO2 balloons, soda cans
All roasts reference your actual data with a mini receipt panel:
- Failure rate analysis (any % triggers something)
- Instant failures (<10s) with job name
- Slow painful failures (hours then FAILED) with job name
- Array job burst detection
- Night owl patterns (10pm–6am submissions)
- Weekend warrior detection
- Peak submission hour commentary
- Short job inefficiency (<60s completed)
- Single-core job usage
- Memory usage patterns
- Partition loyalty/diversity
- Cancellation habits
- Top CPU hog identification
- Day-of-week patterns (Monday panic, Friday submit-and-pray)
Your shop mascot changes based on total CPU-hours:
| CPU-hours | Examples |
|---|---|
| < 100 | The Lemonade Stand, The Penny Jar |
| 100 – 1K | The Corner Bodega, The Ramen Cart |
| 1K – 10K | The General Store, The Diner |
| 10K – 50K | The Warehouse, The Department Store |
| 50K – 200K | The Mega Depot, The Data Cathedral |
| > 200K | The Compute Empire, The Supercomputer |
usage: slurm-receipt [-h] [--days DAYS] [--user USER] [--start START]
[--end END] [--snap] [--snap-file PATH]
[--no-copy] [--uga] [--demo]
See what your HPC compute really cost.
options:
--days DAYS Days to look back (default: 30)
--user USER Slurm username (default: $USER)
--start START Start date YYYY-MM-DD (overrides --days)
--end END End date YYYY-MM-DD (default: today)
--snap Print receipt + save to ~/slurm_receipt_Nd.txt (no TUI)
--snap-file PATH Save receipt to file
--no-copy Don't auto-copy to clipboard on snap
--uga Add UGA Bulldogs flavor to roasts
--demo Demo with synthetic data (no sacct needed)
The s key saves the receipt and tries to copy to clipboard:
- OSC 52 — works over SSH if your terminal supports it (writes to
/dev/tty) - tmux buffer —
tmux load-buffer(paste withprefix + ]) - xclip / xsel / wl-copy — local clipboard fallback
On quit, the auto-saved receipt location is printed:
Receipt saved to: /home/you/slurm_receipt_30d.txt
MIT