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https://github.com/neboat/pbfs
https://github.com/neboat/pbfs
Last synced: about 1 month ago
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- Host: GitHub
- URL: https://github.com/neboat/pbfs
- Owner: neboat
- License: mit
- Created: 2021-03-03T02:20:25.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2024-11-13T01:41:08.000Z (about 2 months ago)
- Last Synced: 2024-11-13T02:30:02.337Z (about 2 months ago)
- Language: C++
- Size: 3.55 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# README
The bfs program reads in a file storing a binary representation of a graph and executes either BFS or PBFS on that graph.
## Usage
```console
./bfs [-f ] [-a ] [-c]
Flags are:
-f : Specify the name of the test file to use.
-a : Specify the BFS algorithm to use.
Valid values for are:
b for Serial BFS
p for PBFS (default)
-c : Check result for correctness.
```
## Compilation
To compile the bfs executable, simply run:
```console
make
```
The Makefile assumes you have OpenCilk `clang++` and `lld` present in your path for compilation to succeed. You can specify a custom path to OpenCilk `clang++` by setting the `CXX` variable as follows:
```console
make CXX=/path/to/opencilk/bin/clang++
```
You can also set the `EXTRA_CFLAGS` and `EXTRA_LDFLAGS` variables to add or modify the compilation and linking flags, respectively. For example, the following command builds this code with [TCMalloc](https://github.com/google/tcmalloc), if it's installed on your system:
```console
make EXTRA_LDFLAGS="-ltcmalloc"
```
To cleanup the results of make, run:
```console
make clean
```
## Graph input files
The input file to bfs is a binary file with the following format:
```text
<#rows><#columns><#non-zeros>
```
All values except for those in the logical array stored in the binary file are unsigned 32-bit integers. The values in the logical array are stored as doubles. Such a file may be generated for the graph stored in the matrix A using the following MATLAB code*:
```Matlab
[i, j, v] = find(A);
fwrite(f, size(A,1), 'uint32');
fwrite(f, size(A,2), 'uint32');
fwrite(f, nnz(A), 'uint32');
fwrite(f, (i-1), 'uint32');
fwrite(f, (j-1), 'uint32');
fwrite(f, v, 'double');
```
For convenience, this MATLAB code is reproduced in the included MATLAB function `dumpbinsparse(A, output)`, which outputs the matrix `A` into the binary file `output` in the correct format.
## Acknowledgments
Thanks to Aydin Buluc for providing this MATLAB code for creating valid input graphs.
To cite this work, please cite the SPAA paper:
> Charles E. Leiserson and Tao B. Schardl. 2010. A work-efficient parallel breadth-first search algorithm (or how to cope with the nondeterminism of reducers). In Proceedings of the twenty-second annual ACM symposium on Parallelism in algorithms and architectures (SPAA '10). Association for Computing Machinery, New York, NY, USA, 303–314. https://doi.org/10.1145/1810479.1810534
```bibtex
@inproceedings{LeisersonSc10,
author = {Leiserson, Charles E. and Schardl, Tao B.},
title = {A work-efficient parallel breadth-first search algorithm (or how to cope with the nondeterminism of reducers)},
year = {2010},
isbn = {9781450300797},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/1810479.1810534},
doi = {10.1145/1810479.1810534},
booktitle = {Proceedings of the Twenty-Second Annual ACM Symposium on Parallelism in Algorithms and Architectures},
pages = {303–-314},
numpages = {12},
keywords = {breadth-first search, cilk, graph algorithms, hyperobjects, multithreading, nondeterminism, parallel algorithms, reducers, work-stealing},
location = {Thira, Santorini, Greece},
series = {SPAA '10}
}
```