MapLib

MapLib provides algorithms for generating mapping of processing elements to processor unities to three 3-D topologies: mesh, torus, and HAEC Box. MapLib implements: (i) Communication- and topology-oblivious mapping strategies, which do not take into account the communication matrices of the applications nor the target processor topologies. These algorithms follow a predetermined node ordering to map all processes to the available nodes and produce deterministic mappings. (ii) Communication- and topology-aware mapping strategies, which consider both communication matrices of the applications and target processor topologies. These algorithms produce different mappings for a given application–system pair.

Paper references

[J. H. M. Korndörfer, M. Bielert, L. L. Pilla, and F. M. Ciorba, Mapping matters: Application process mapping on 3-d processor topologies, arXiv preprint arXiv:2005.10413 (2020).](https://arxiv.org/abs/2005.10413)
Paper presentation recording: https://drive.switch.ch/index.php/s/VaO9f7zT79lvRe2

MapLib contains the following process mapping techniques:

Communication- and Topology-Oblivious Mapping:

Peano

Hilbert

Gray

sweep

scan

Communication- and Topology-Aware Mapping:

Bokhari

topo-aware

greedy

FHgreedy

greedyALLC

bipartition

PaCMap

The folder mapping-matters-commMatrices contains all input communication matrices

and

The folder mapping-matters-Mappings contains all mappings that were used in the paper:

Mapping Matters: Application Process Mapping on 3-D Processor Topologies available at: https://arxiv.org/abs/2005.10413

The sub-folder MapLib contains all Python files where mapping.py and mapping_compl.py consist of the implemented mapping algorithms.

To install the program:

Run make
Run pip3 install --editable .

As an example of how to use the library, one can run the provided wrapper.sh script

Acknowledgments

Acknowledgment to Daniel Besmer and Viacheslav Sharunov for their earlier contribution to the library.

License

unibas-dmi-hpc/MapLib

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