Caffeine VS linux

/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

That, and also when caffeine came out it replaced one of the major uses (caching) of guava.

https://github.com/ben-manes/caffeine

I decided to start with an overview of what open-source options are currently available. When it comes to the implementation of the on-heap cache mechanism, the options are numerous – there is well known: guava, ehcache, caffeine and many other solutions. However, when I began researching cache mechanisms offering the possibility of storing data outside GC control, I found out that there are very few solutions left. Out of the popular ones, only Terracotta is supported. It seems that this is a very niche solution and we do not have many options to choose from. In terms of less-known projects, I came across Chronicle-Map, MapDB and OHC. I chose the last one because it was created as part of the Cassandra project, which I had some experience with and was curious about how this component worked:

Visit the official Caffeine git project and documentation here for more information if you are interested in the subject.

not to distract from your valid points but, when used properly, Caffeine + Reactor can work together really nicely [1].

[1] https://github.com/ben-manes/caffeine/tree/master/examples/c...

Yes, I think that is my main concern in that often research papers do not disclose the weaknesses of their approaches and the opposing tradeoffs. There is no silver bullet.

The stress workload that I use is to chain corda-large [1], 5x loop [2], corda-large at a cache size of 512 entries and 6M requests. This shifts from a strongly LRU-biased pattern to an MRU one, and then back again. My solution to this was to use hill climbing by sampling the hit rate to adaptively size of the admission window (aka your FIFO) to reconfigure the cache region sizes. You already have similar code in your CACHEUS implementation which built on that idea to apply it to a multi-agent policy.

Caffeine adjusts the frequency comparison for admission slightly to allow ~1% of losing warm candidates to enter the main region. This is to protect against hash flooding attack (HashDoS) [3]. That isn't intended to improve or correct the policy's decision making so should be unrelated to your observations, but an important change for real-world usage.

I believe LIRS2 [4] adaptively sizes their LIR region, but I do not recall the details as a complex algorithm. It did very well across different workloads when I tried it out and the authors were able to make a few performance fixes based on my feedback. Unfortunately I find LIRS algorithms to be too difficult to maintain for an industry setting because while excellent, the implementation logic is not intuitive which makes it frustrating to debug.

[1] https://github.com/ben-manes/caffeine/blob/master/simulator/...

A lot of Guava's most popular libraries graduated to the JDK. Also Caffeine is the evolution of our c.g.common.cache library. So you need Guava less than you used to. Hooray!

Unfortunately, I don't gather statistics on the demonstration server. I believe that the in-memory caffeine cache (https://github.com/ben-manes/caffeine) saved me.

Caffeine is a Java cache that uses a 4-bit count-min sketch to estimate the popularity of an entry over a sample period. This is used by an admission filter (TinyLFU) to determine whether the new arrival is more valuable than the LRU victim. This is combined with hill climbing to optimize how much space is allocated for frequency vs recency. That results in an adaptive eviction policy that is space and time efficient, and achieves very high hit rates.

These are a bit easier to see what's going on:

https://github.com/torvalds/linux/commit/d5cf50dafc9dd5faa1e...

https://github.com/torvalds/linux/blob/d5cf50dafc9dd5faa1e61...

Unfortunately Github doesn't have a way to render symbols for whitespace, but you can tell by selecting the spaces that the previous version had leading tabs. Linus changed it so that the tokens `default` and the number e.g. `12` are also separated by a tab. This is tricky, because the token "default" is seven characters, it will always give this added tab a width of 1 char which makes it always layout the same as if it were a space no matter if you use tab widths of 1, 2, 4, or 8.

There was also a Gentoo effort to run atop FreeBSD[0]. The challenge of course is that afaik none of the BSD kernel ABIs are considered stable. The stable interface is the BSD libc. That said, with binfmt_misc, I don't see a reason you couldn't just run (at least some) FreeBSD binaries on Linux with a thin syscall translation layer (rather something like qemu-system) and then your layer hooked via binfmt_misc. I'm not aware of anyone who has done this for FreeBSD, but prior efforts existed as alternate binfmts for SysVr4/5 ELF binaries[2]. Either way would take some elbow grease, but you *might* even be able just reuse binfmt_elf and just have a new interpreter for FreeBSD elf.

[0] https://wiki.gentoo.org/wiki/Gentoo_FreeBSD

[1] https://docs.kernel.org/admin-guide/binfmt-misc.html

[2] https://github.com/torvalds/linux/blob/master/fs/binfmt_elf....

> The original less-than check was deemed incorrect

It was only deemed incorrect because of an information leak. Not because it's a valid use-case for user space to copy smaller portions of *hwrpb into user space. https://github.com/torvalds/linux/commit/21c5977a836e399fc71...

Correct. And the combined work needs to carry the MIT license text and copyright attributions for the MIT software authors. With binary distribution it must also be overt, not hidden in some source code drop, but directly accompanying the binary.

Many people who talk about relicensing never credit the MIT developers or distribute the MIT license text. "Because it's GPL now."

I don't think that you believe that, but many developers do.

Some don't see the need for source code scans for Open Source compliance, because the license.txt says GPL, so it's GPL. Prime example is the Linux kernel. There is code under different licenses in there, but people don't even read https://github.com/torvalds/linux/blob/master/COPYING till the end ("In addition, other licenses may also apply.") and conclude it's simply GPL 2 and nothing else.

Also be aware that sublicensing is not the same as relicensing.

> Does he have something against it?

He notoriously hates GNU Emacs, yes.

https://marc.info/?m=122955159617722

https://github.com/torvalds/linux/blob/master/Documentation/...

So If we would only count code and not comments, it is only 9489 LoC Rust. Which would be about 0.03% and if we take all lines and not only LoC it would be around 0.05%

[0] https://github.com/XAMPPRocky/tokei

[1] https://github.com/torvalds/linux/commit/b401b621758e46812da...

AIUI fsync is built on futex_waitv which has been upstreamed. So this has to be more than that.

https://github.com/torvalds/linux/commit/a0eb2da92b715d0c97b...

git clone --no-checkout --depth 1 https://github.com/torvalds/linux.git $dir