This document describes an attempt to develop a compiler-based approach for computations with symmetric tensors. Given a computation and the symmetries of its input tensors, we derive formulas for random access under a storage scheme that eliminates redundancies; construct intermediate representations to describe the loop structure; and translate this information, using the taco tensor algebra compiler, into code. While we achieve a framework for reasoning about a fairly general class of symmetric computations, the resulting code is not performant when the symmetries are misaligned.
@article{arxiv.2110.00186,
title = {An Attempt to Generate Code for Symmetric Tensor Computations},
author = {Jessica Shi and Stephen Chou and Fredrik Kjolstad and Saman Amarasinghe},
journal= {arXiv preprint arXiv:2110.00186},
year = {2021}
}