Published March 14, 2023 | Version v1
Software Open

Code and data for the ICAPS 2023 paper "Finding Matrix Multiplication Algorithms with Classical Planning"

  • 1. Linköping University



The file contains the planners we used to find algorithms for matrix multiplication. See the included readme file for more information.


The file contains generators for generating pddl and sas planning problems for finding matrix multiplicative algorithms.

Experiment data

The file contains the raw data, parsed values, scripts and basic reports of the presented experiments.


This work was partially supported by TAILOR, a project funded by the EU Horizon 2020 research and innovation programme under grant agreement no. 952215, and by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation. The computations were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) and the Swedish National Infrastructure for Computing (SNIC), partially funded by the Swedish Research Council through grant agreements no. 2022-06725 and no. 2018-05973.


Files (67.4 MB)

Name Size Download all
17.0 MB Preview Download
50.5 MB Preview Download

Additional details


TAILOR – Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization 952215
European Commission