# Graph-based Algorithms for Linear Computation Coding

arXiv: https://arxiv.org/abs/2401.08249 · HTML: https://mlsanity.com/paper/2401.08249/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Jan 2024.

## Built on by (most cited first, 1 of 1)

- [Coding for Computation: Efficient Compression of Neural Networks for Reconfigurable Hardware](https://mlsanity.com/paper/2504.17403/) (2025)

## Abstract (arXiv)

We revisit existing linear computation coding (LCC) algorithms, and introduce a new framework that measures the computational cost of computing multidimensional linear functions, not only in terms of the number of additions, but also with respect to their suitability for parallel processing. Utilizing directed acyclic graphs, which correspond to signal flow graphs in hardware, we propose a novel LCC algorithm that controls the trade-off between the total number of operations and their parallel executability. Numerical evaluations show that the proposed algorithm, constrained to a fully parallel structure, outperforms existing schemes.