Symmetric Locality: Definition and Initial Results

TL;DR

This paper introduces the concept of symmetric locality, generalizes known data reuse patterns, and provides a framework to enhance cache and memory performance in high-performance computing applications.

Contribution

It defines symmetric locality, extends existing results to general re-traversals, and offers an abstract framework for improving memory performance in compilers and machine learning.

Findings

Generalized symmetric locality for any re-traversal

Connected cyclic and sawtooth traces to symmetric locality

Framework applicable to compiler design and machine learning

Abstract

In this short paper, we characterize symmetric locality. In designing algorithms, compilers, and systems, data movement is a common bottleneck in high-performance computation, in which we improve cache and memory performance. We study a special type of data reuse in the form of repeated traversals, or re-traversals, which are based on the symmetric group. The cyclic and sawtooth traces are previously known results in symmetric locality, and in this work, we would like to generalize this result for any re-traversal. Then, we also provide an abstract framework for applications in compiler design and machine learning models to improve the memory performance of certain programs.