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autotuning_methodology

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1.0.0 autotuning_methodology-1.0.0-py3-none-any.whl

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Project: autotuning_methodology
Version: 1.0.0
Filename: autotuning_methodology-1.0.0-py3-none-any.whl
Download: [link]
Size: 51162
MD5: 90ff4a9a5355c6acc27bdb87d59687a0
SHA256: f242c782dfd03757e6aba9261733565140b771f2a1305132df615a1094e0858f
Uploaded: 2024-05-31 10:32:01 +0000

dist-info

METADATA · WHEEL · RECORD · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: autotuning_methodology
Version: 1.0.0
Summary: Software package easing implementation of the guidelines of the 2024 paper 'A Methodology for Comparing Auto-Tuning Optimization Algorithms' (https://doi.org/10.1016/j.future.2024.05.021). The DOI of this software is https://doi.org/10.5281/zenodo.11243974.
Author-Email: Floris-Jan Willemsen <fjwillemsen97[at]gmail.com>
Project-Url: Bug Tracker, https://github.com/fjwillemsen/autotuning_methodology/issues
Project-Url: Documentation, https://fjwillemsen.github.io/autotuning_methodology/
Project-Url: Repository, https://github.com/fjwillemsen/autotuning_methodology
Keywords: autotuning,auto-tuning,methodology,scientific
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Python: >=3.9
Requires-Dist: numpy (>=1.22.4)
Requires-Dist: scipy (>=1.10.1)
Requires-Dist: scikit-learn (>=1.0.2)
Requires-Dist: matplotlib (>=3.7.1)
Requires-Dist: yappi (>=1.4.0)
Requires-Dist: progressbar2 (>=4.2.0)
Requires-Dist: jsonschema (>=4.17.3)
Requires-Dist: nonconformist (>=2.1.0)
Requires-Dist: kernel_tuner (>=1.0.0b5)
Requires-Dist: pylint (>=2.14.4); extra == "dev"
Requires-Dist: black (>=23.3.0); extra == "dev"
Requires-Dist: sphinx (>=7.2.1); extra == "docs"
Requires-Dist: sphinx_rtd_theme (>=2.0.0); extra == "docs"
Requires-Dist: sphinx-pyproject (>=0.3.0); extra == "docs"
Requires-Dist: ruff (>=0.0.263); extra == "test"
Requires-Dist: pep440 (>=0.1.2); extra == "test"
Requires-Dist: pytest (>=7.3.1); extra == "test"
Requires-Dist: pytest-cov (>=4.0.0); extra == "test"
Requires-Dist: nox (>=2023.4.22); extra == "test"
Requires-Dist: crepes (>=0.2.0); extra == "test"
Requires-Dist: tomli (>=2.0.1); extra == "test"
Provides-Extra: dev
Provides-Extra: docs
Provides-Extra: test
Description-Content-Type: text/markdown
[Description omitted; length: 8008 characters]

WHEEL

Wheel-Version: 1.0
Generator: flit 3.9.0
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
autotuning_methodology/__init__.py sha256=tk0q-B6HEHC8vGSITzeV5b1v2_ZgAdf3QddtEyfcLOA 95
autotuning_methodology/baseline.py sha256=HLBTW6RoHaXqnrIpFw7xmVZtceiXbKcqeqmOwy5UtJE 17647
autotuning_methodology/caching.py sha256=VcYk4Ph01SR-79LHZ-m8DE62wjTMJ0dxX23ba6XfOGU 8418
autotuning_methodology/curves.py sha256=pQAjx-HVBWCffwI_rQCVnovG11A_7TGM-kr3T7IDHaM 51986
autotuning_methodology/experiments.py sha256=q27CZ2hwmNZjcAJHEk3zzYKKRvYVemff2YnplhInjfI 9832
autotuning_methodology/runner.py sha256=mk2cRZwOFrrsdKdqG-UxwvOJUMgiWN2smkxfm1GOviU 24377
autotuning_methodology/schema.json sha256=HxdBBVCY4hsrE3dsGlF5cGEKYHS6tYYgLv-CxjF40ZY 4138
autotuning_methodology/searchspace_statistics.py sha256=MGM214QT9I99jpzBpfkxKF5rQ2z46wx4o06-wF774GE 25701
autotuning_methodology/validators.py sha256=N5uUaE_rMFF6ZxDzWuBoGI2tPG-A6kroKKozVFvaDPc 1787
autotuning_methodology/visualize_experiments.py sha256=9BxOCrPEPPrg_VzaswMGCERoLVDliFlEiSxcLrZkKlE 48490
autotuning_methodology-1.0.0.dist-info/entry_points.txt sha256=GSR6-nkntWQGuOBzPR94OSVUQG4XJibjmZubiWXzylc 166
autotuning_methodology-1.0.0.dist-info/LICENSE sha256=F53xUaSOESu7crHw0-zm4sqFlqHkSjRz7MWSmHfMNGA 1077
autotuning_methodology-1.0.0.dist-info/WHEEL sha256=EZbGkh7Ie4PoZfRQ8I0ZuP9VklN_TvcZ6DSE5Uar4z4 81
autotuning_methodology-1.0.0.dist-info/METADATA sha256=0eosh6bNlbqQWkx8OL0LwdjOuxYRxnhWHDtMoxDt5W8 10102
autotuning_methodology-1.0.0.dist-info/RECORD — —

entry_points.txt

[console_scripts]
autotuning_experiment = autotuning_methodology.experiments:entry_point
autotuning_visualize = autotuning_methodology.visualize_experiments:entry_point