libCacheSim VS sosp23-s3fifo

https://github.com/1a1a11a/libCacheSim/blob/develop/libCache...

/u/someplaceguy,

Those LIRS traces, along with many others, available at this page [1]. I did a cursory review using their traces using Caffeine's and the author's simulators to avoid bias or a mistaken implementation. In their target workloads Caffeine was on par or better [2]. I have not seen anything novel in this or their previous works and find their claims to be easily disproven, so I have not implement this policy in Caffeine simulator yet.

[1]: https://github.com/ben-manes/caffeine/wiki/Simulator

[2]: https://github.com/1a1a11a/libCacheSim/discussions/20

We observed that quick demotion[2] is important to achieve a low miss ratio in modern cache workloads, and existing algorithms such as TinyLFU and LIRS have lower miss ratios because of the small 1% window they use. This motivated us to design S3-FIFO, which uses simple FIFO queues to achieve low miss ratios. It is true that compared to state-of-the-art, S3-FIFO does not use any fancy techniques, but this does not mean it has bad performance.

In our large-scale evaluations, we found that the fancy techniques in LIRS, ARC, and TinyLFU can sometimes increase the miss ratio. But simple FIFO queues are more robust. However, *it is not true that S3-FIFO is better on every trace*.

* Note that some of the S3-FIFO results in Otter's repo are not updated and have an implementation bug, and we are working with the owner to update them.

[1] https://github.com/Thesys-lab/sosp23-s3fifo?tab=readme-ov-fi...