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.