https://github.com/lorenzhs/sampling
Efficient Random Sampling: Parallel, Vectorized, Cache-Efficient, and Online
https://github.com/lorenzhs/sampling
Last synced: about 2 months ago
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Efficient Random Sampling: Parallel, Vectorized, Cache-Efficient, and Online
- Host: GitHub
- URL: https://github.com/lorenzhs/sampling
- Owner: lorenzhs
- License: other
- Created: 2017-12-08T12:47:26.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2024-03-08T12:03:57.000Z (over 1 year ago)
- Last Synced: 2024-11-01T08:42:13.970Z (7 months ago)
- Language: C++
- Homepage:
- Size: 794 KB
- Stars: 10
- Watchers: 6
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
## Efficient Random Sampling [](https://travis-ci.org/lorenzhs/sampling)
#### Parallel, Vectorized, Cache-Efficient, and Online
This is the code to accompany our eponymous paper: *Sanders, P., Lamm, S., Hübschle-Schneider, L., Schrade, E. and Dachsbacher, C., 2018. Efficient Parallel Random Sampling—Vectorized, Cache-Efficient, and Online. ACM Transactions on Mathematical Software (TOMS), 44.3 (2018): 29.*
You can find the freely accessible author's version [in the arXiv](https://arxiv.org/abs/1610.05141).
If you use this library in the context of an academic publication, we ask that you cite our paper:
```bibtex
@article{sanders2018sampling,
title = {Efficient Parallel Random Sampling---Vectorized, Cache-Efficient, and Online},
author = {Sanders, Peter and Lamm, Sebastian and H{\"u}bschle-Schneider, Lorenz
and Schrade, Emanuel and Dachsbacher, Carsten},
journal = {ACM Trans. Math. Softw.},
year = {2018},
issn = {0098-3500},
volume = {44},
number = {3},
articleno = {29},
pages = {29:1--29:14},
issue_date = {April 2018},
publisher = {ACM},
doi = {10.1145/3157734}
}
```
### Building
Build with cmake (version 2.8.12 or later is required). Remember to fetch the submodules before compiling: `git submodule update --init`. A compiler compatible with C++11 is required.
**Optional Dependencies:** An MPI library for Algorithm P's test runner (Algorithm P itself is implemented independently of MPI), Intel Math Kernel Library (MKL) for faster random variate generation
### Tests
To run the tests, set the cmake variable `SAMPLING_BUILD_TESTS` to `ON`. Make sure that the `extlib/googletest` submodule is present. Build, then execute the tests with `ctest`.
We plan to make the test suite more comprehensive in the future.
**[License](/LICENSE):** 2-clause BSD