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Framework for transforming raw CUDA-based simulation logs into structured datasets with reusable schemas and minimal visualization for verification.

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Steps to run Heat2D MASS simulation

1) Build once

make develop LLVM_PREBUILD_DOWNLOAD_URL=https://github.com/llvm/llvm-project/releases/download/llvmorg-14.0.6/clang+llvm-14.0.6-x86_64-linux-gnu-rhel-8.4.tar.xz
make build

Notes:

  • make develop is one-time setup (rerun only if toolchain/deps change).
  • Rebuild with make build only when C++/CUDA sources change; skip for Python/README edits.

2) Run the simulation (manual)

Use --help to see parameters. You must use --verbose to print the grid. Example:

./bin/Heat2D_PlaceV2 --interval 1 --verbose

Max size as of MASS v0.7.2, this implementation as of 5/10/2024, is 3083.

3) Visualize using run.sh (recommended)

run.sh runs the full pipeline:

  1. Run the simulation and write log.txt.
  2. Parse log.txt into heat2d_long.csv and heat2d_grids.npz.
  3. Install Plotly if needed.
  4. Launch visualize_plotly.py.

Run it like this:

sh run.sh

4) Visualize manually (optional)

If you want to run each step yourself:

./bin/Heat2D_PlaceV2 --interval 1 --verbose > log.txt
python3 parse_heat2d.py
python3 -m pip install --user plotly
python3 visualize_plotly.py

5) Optional: simviz build

make build-simviz
./bin/simviz heat2d.viz

Python virtual environment (UB)

If you are on UB, you can create a Python virtual environment to isolate packages:

python3 -m venv .venv
source .venv/bin/activate
python3 -m pip install --upgrade pip
python3 -m pip install plotly

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Framework for transforming raw CUDA-based simulation logs into structured datasets with reusable schemas and minimal visualization for verification.

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