thundergbm
ThunderGBM: Fast GBDTs and Random Forests on GPUs
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Download Latest Version (.zip)- machine.conf
- test_dataset.txt
- test_dataset.txt.group
- default.css
- lang-logo-tgbm.png
- overall.png
- tgbm-logo.png
- conf.py
- faq.md
- how-to.md
- index.md
- make.bat
- Makefile
- parameters.md
- README.md
- requirements.txt
- exact_tree_builder.h
- function_builder.h
- hist_tree_builder.h
- hist_tree_builder_single.h
- shard.h
- tree_builder.h
- metric.h
- multiclass_metric.h
- pointwise_metric.h
- ranking_metric.h
- multiclass_obj.h
- objective_function.h
- ranking_obj.h
- regression_obj.h
- cub_wrapper.h
- device_lambda.cuh
- log.h
- multi_device.h
- booster.h
- common.h
- config.h.in
- dataset.h
- hist_cut.h
- ins_stat.h
- parser.h
- predictor.h
- quantile_sketch.h
- row_sampler.h
- sparse_columns.h
- syncarray.h
- syncmem.h
- trainer.h
- tree.h
- __init__.py
- base_model.py
- catboost_model.py
- datasets.py
- lightgbm_model.py
- thundergbm_model.py
- xgboost_model.py
- __init__.py
- data_utils.py
- file_utils.py
- convert_dataset_plk.py
- experiments.py
- README.md
- run_exp.sh
- thundergbm-0.3.12-py2-none-win_amd64.whl
- thundergbm-0.3.12-py3-none-win_amd64.whl
- thundergbm-0.3.16-py3-none-any.whl
- thundergbm-0.3.4-py3-none-win_amd64.whl
- classification_demo.py
- ranking_demo.py
- regression_demo.py
- __init__.py
- thundergbm.py
- LICENSE
- README.md
- requirements.txt
- setup.py
- gbm.R
- README.md
- CMakeLists.txt
- googletest
- test_csr2csc.cpp
- test_cub_wrapper.cu
- test_dataset.cpp
- test_for_refactor.cpp
- test_gbdt.cpp
- test_get_cut_point.cpp
- test_gradient.cu
- test_main.cpp
- test_metrics.cpp
- test_parser.cpp
- test_synarray.cpp
- test_synmem.cpp
- test_tree.cpp
- exact_tree_builder.cu
- function_builder.cu
- hist_tree_builder.cu
- hist_tree_builder_single.cu
- shard.cu
- tree_builder.cu
- metric.cu
- multiclass_metric.cu
- pointwise_metric.cu
- rank_metric.cpp
- multiclass_obj.cu
- objective_function.cu
- ranking_obj.cpp
- common.cpp
- log.cpp
- CMakeLists.txt
- dataset.cpp
- gbm_R_interface.cpp
- hist_cut.cu
- parser.cpp
- predictor.cu
- quantile_sketch.cpp
- row_sampler.cu
- scikit_tgbm.cpp
- sparse_columns.cu
- syncmem.cpp
- thundergbm_predict.cpp
- thundergbm_train.cpp
- trainer.cu
- tree.cu
- .gitignore
- .gitmodules
- CMakeLists.txt
- cub
- LICENSE
- README.md
- thundergbm-full.pdf
π Installation Guide
1. Get the code
git clone https://github.com/Xtra-Computing/thundergbm
Downloads the entire project code from GitHub to your computer.
cd thundergbm
Moves into the project folder you just downloaded.
2. CMake
Medium RecommendedPrerequisites
mkdir build && cd build && cmake .. && make -j
Creates a folder to hold the build output and moves into it.
Check that an executable was created inside the build folder, then run it directly (e.g. ./build/app_name).
Pulled directly from this repo's README.
3. Python
EasyPrerequisites
* `pip install thundergbm`
Installs the Python libraries listed in requirements.txt (or similar).
* `pip install thundergbm-0.3.4-py3-none-win_amd64.whl`
Installs the Python libraries listed in requirements.txt (or similar).
If it runs without errors and prints output in the terminal, it worked.
Pulled directly from this repo's README.
4. Make
MediumPrerequisites
- Git Needed to download the project code from GitHub.
- Make Usually pre-installed on Linux/macOS. On Windows, install separately (e.g. via MSYS2 or WSL).
cd docs
This project's files live in a subfolder, so move into it first.
make
Compiles the code based on the generated build configuration to produce an executable.
If it finishes without errors, it worked. Try running the generated executable directly.
// repository documentation
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