HOTL

Author:

Xiang Xiaoya1,Ding Chen1,Luo Hao1,Bao Bin2

Affiliation:

1. University of Rochester, Rochester, NY, USA

2. Adobe Systems Incorporated, Waltham, MA, USA

Abstract

The locality metrics are many, for example, miss ratio to test performance, data footprint to manage cache sharing, and reuse distance to analyze and optimize a program. It is unclear how different metrics are related, whether one subsumes another, and what combination may represent locality completely. This paper first derives a set of formulas to convert between five locality metrics and gives the condition for correctness. The transformation is analogous to differentiation and integration used to convert between higher order polynomials. As a result, these metrics can be assigned an order and organized into a hierarchy. Using the new theory, the paper then develops two techniques: one measures the locality in real time without special hardware support, and the other predicts multicore cache interference without parallel testing. The paper evaluates them using sequential and parallel programs as well as for a parallel mix of sequential programs.

Publisher

Association for Computing Machinery (ACM)

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Multi-Tenant In-Memory Key-Value Cache Partitioning Using Efficient Random Sampling-Based LRU Model;IEEE Transactions on Cloud Computing;2023-10

2. Precise event sampling‐based data locality tools for AMD multicore architectures;Concurrency and Computation: Practice and Experience;2023-04-03

3. ReuseTracker : Fast Yet Accurate Multicore Reuse Distance Analyzer;ACM Transactions on Architecture and Code Optimization;2022-03-31

4. Low-Overhead Reuse Distance Profiling Tool for Multicore;Euro-Par 2021: Parallel Processing Workshops;2022

5. Efficient Modeling of Random Sampling-Based LRU;50th International Conference on Parallel Processing;2021-08-09

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