Robust Learning-Augmented Caching: An Experimental Study

06/28/2021
by   Jakub Chłędowski, et al.
0

Effective caching is crucial for the performance of modern-day computing systems. A key optimization problem arising in caching – which item to evict to make room for a new item – cannot be optimally solved without knowing the future. There are many classical approximation algorithms for this problem, but more recently researchers started to successfully apply machine learning to decide what to evict by discovering implicit input patterns and predicting the future. While machine learning typically does not provide any worst-case guarantees, the new field of learning-augmented algorithms proposes solutions that leverage classical online caching algorithms to make the machine-learned predictors robust. We are the first to comprehensively evaluate these learning-augmented algorithms on real-world caching datasets and state-of-the-art machine-learned predictors. We show that a straightforward method – blindly following either a predictor or a classical robust algorithm, and switching whenever one becomes worse than the other – has only a low overhead over a well-performing predictor, while competing with classical methods when the coupled predictor fails, thus providing a cheap worst-case insurance.

READ FULL TEXT
research
09/07/2022

Computing the Hit Rate of Similarity Caching

Similarity caching allows requests for an item i to be served by a simil...
research
05/28/2020

Better and Simpler Learning-Augmented Online Caching

Lykouris and Vassilvitskii (ICML 2018) introduce a model of online cachi...
research
10/22/2022

Algorithms with Prediction Portfolios

The research area of algorithms with predictions has seen recent success...
research
03/04/2020

Online metric algorithms with untrusted predictions

Machine-learned predictors, although achieving very good results for inp...
research
11/03/2020

Beyond Worst-case Analysis of Multicore Caching Strategies

Every processor with multiple cores sharing a cache needs to implement a...
research
02/15/2018

Competitive caching with machine learned advice

Traditional online algorithms encapsulate decision making under uncertai...
research
07/02/2021

Ascent Similarity Caching with Approximate Indexes

Similarity search is a key operation in multimedia retrieval systems and...

Please sign up or login with your details

Forgot password? Click here to reset