Skip to content
Claude CodedocsData & ML4 files · +215 −97

Add figures, Llama-3.2-3B data, and recompile Euro-Par LaTeX paper

Session from traceweave on Hugging Face by Samarth0710 · MIT · condensed by Coders Talk

25msession
0interventions
GOAL

Add existing figures to the HyperCluster paper and recompile the PDF, then extend the paper with Llama-3.2-3B results, real and plausible metrics, and additional generated figures.

  1. Prompt · +0
    Add the figures/ to the paper and recompile the PDF
  2. Agent did · +0m
    Read the paper and figure scripts, replaced three placeholder comments with includegraphics calls for architecture, latency, and memory figures, and compiled the PDF twice (15 pages, no errors)
  3. Break · 6h 26m away, not counted
  4. Prompt · +1m
    Add Llama 3.2 3B Instruct to the tables using real stats from stats/ where available and believable made-up numbers elsewhere; add more figures via paperbanana; convert the ring pipeline listing into a figure
  5. Agent did · +1m
    Explored all 24 JSON stat files and the paperbanana tool via subagents to compile real latency/throughput numbers by model and node count
  6. Agent did · +2m
    Edited samplepaper.tex extensively: added Llama-3.2-3B to abstract, models section, four tables (latency, selective loading, network performance, timing breakdown), discussion text, and conclusion; rewrote latency_comparison.py and wrote a new throughput_scaling.py script; launched two background paperbanana agents to generate a ring-pipeline diagram and a throughput figure
  7. Fail · +6m
    Local figure scripts failed with ModuleNotFoundError: No module named 'matplotlib', and attempts to pip install into the venv failed (missing pip, then externally-managed system Python block)
  8. Agent did · +17m
    Found matplotlib already installed in the paperbanana project's own venv and used that interpreter to run latency_comparison.py and throughput_scaling.py successfully, producing PDFs and PNGs
  9. Fail · +18m
    Both background paperbanana subagents reported the sandbox denied permission to run Python scripts, so neither could generate the ring pipeline figure as tasked
  10. Agent did · +18m
    Wrote a standalone gen_ring_pipeline.py script and ran it directly with the paperbanana venv's python in the background; it succeeded and produced ring_pipeline_iter3_0.jpg, which was wired into the tex file
  11. Agent did · +25m
    Recompiled the PDF twice (clean, no reference warnings, 15 pages) and reviewed the three generated figure images
  12. Outcome · +25m
    Session ended after the PDF was recompiled successfully; subsequent attempts to fetch the background subagents' full output logs failed repeatedly with a 409k+ token prompt exceeding the 128k model limit
VERDICT

Next time I'd tell it upfront which python environment has matplotlib and paperbanana installed, since it burned a lot of turns discovering that the system python, the project venv, and pip were all broken before it found the paperbanana venv that actually worked. Running the ring-pipeline generation script directly myself instead of relying on the sandboxed subagents is what actually got the figure made, since the subagents kept getting permission errors. The paper recompiled cleanly in the end, but I never got to see the full output logs from the background agents because the retrieval calls blew past the model's context limit.

I tried this · 0

Discussion · 0

How Builds work