By the way, if you're using mmtests for benchmarking, some results are marked significant (with asterisks) and some are not.

not significant: 17.74 ( -3.72%)
significant: 132.26 * -15.92%*

I assumed the asterisk would have some meaning, but didn't exactly know what it is until I read the code: "significant" means their (baseline and new) confidence intervals do not overlap.

When the variance is high and the number of observations is low, many results may not be marked as significant. However, that doesn’t necessarily mean the results can simply be ignored (?)

Still digesting it, and may be slightly incorrect, but a summary of what I've learned: properly using statistics to compare the performance of computer systems [1] [2].

0. When you get a sample and calculate sample mean, it is likely different from the population mean. Simply comparing two sample means from different computer systems may therefore lead to misleading conclusions, since the observed difference could be due to random sampling variation rather than a real performance difference (especially when the variance is high).

1. Central Limit Theorem indicates that, regardless of the underlying distribution, the sampling distribution of the mean tends to follow normal distribution when the sample size is sufficiently large (typically n >= 30). But to apply CLT, the observations should be independent and collected from the same distribution.

2. Based on the CLT, we can estimate how close the sample mean (to be precise, any population parameter) is likely to be to the population mean. A confidence interval [x, y] with a confidence level of p% means that if we repeated the sampling process many times under the same conditions, about p% of those intervals would contain the population mean.

3. To compare two distributions, confidence intervals can help determine whether the difference between mean values is statistically significant. This can be done by:

- Checking whether the confidence intervals of the two samples do not overlap, or
- Examining the confidence interval for the mean of the differences to check if it does not include 0.

4. Caveat: The CLT assumes that the data is collected independently, meaning one observation does not affect another. In computer systems, this assumption usually does not hold. Caches, memory layout, scheduling decisions etc. can introduce some degree of dependencies between observations.

This can be mitigated by 1) reducing dependence between experiments as much as possible or 2) by applying the bootstrapping method [3].

[1] Jan Kara, Measuring performance regressions, https://youtu.be/HAHhW13ofrg?si=drgegMwXUDegHsQf
[2] Dev Jain, The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling, https://www.amazon.com/Art-Computer-Systems-Performance-Analysis/dp/0471503363
[3] https://en.wikipedia.org/wiki/Bootstrapping_(statistics)

@vbabka @ljs @wagi

right, no matter how many transistors you throw into a cache.

@wagi @ljs

I have a bigger, scalable bookshelf and I ordered small one to use it like a cache for a larger bookshelf but turns out the cache was too small :P

@ljs it's so sad that the bookshelf isn't big enough to fit the best book!

Got a new small bookshelf but the user experience isn’t great

@conor @ljs @vbabka

Haha yeah, quite nice (watching my legs tremble)

@ljs @vbabka /me prepares to go out

@vbabka @ljs do you?

@vbabka nah 5am gym sounds like @ljs !

@oleksandr didn’t refuse anything :’(
Perhaps should have refused a looong nap at night before 2am call

@vbabka just woke up from hibernation right now uh

Oh god let me fall asleep

@sj recently started using drgn to add more DAMON selftests, which is a super interesting use case that I didn't envision: https://lore.kernel.org/all/20250628160428.53115-1-sj@kernel.org/. It has already found a real bug! https://lore.kernel.org/all/20250719181932.72944-1-sj@kernel.org/

@oleksandr @vbabka

SLAIB?

size = ai_prompt("Size sufficient to fit five integers");
gfp = ai_prompt("Appropriate GFP flags for the current context?");
array = kmalloc(size, gfp);

linux-stable is a vibe-backported frankenkernel

All microconferences (MCs) at LPC 2025 have been accepted! It is time to submit topics to your favorite MCs.

Please check out our latest blog post for the list of MCs, and how to create a ideal MC topic.

https://lpc.events/blog/current/index.php/2025/07/25/all-microconferences-have-been-accepted/

I've been playing with the LLM code assistants, trying to stress them out with the Linux kernel code. So far, I've had success with them writing reasonable unit tests:
https://lore.kernel.org/lkml/20250717085156.work.363-kees@kernel.org/
https://lore.kernel.org/lkml/20250724030233.work.486-kees@kernel.org/
These both saved me some time since it emitted quite a lot of good boundary testing code, but I had to massage them both a bit until I was happy with the coverage. But it was a net win on time spent.

And then I walked it through fixing a buffer overflow. This one didn't save me any time because I had to tell it how to look at the problem. Since it was a shorter/simpler session, I included my exact prompts just for anyone interested in what I did:
https://lore.kernel.org/lkml/20250724080756.work.741-kees@kernel.org/

@ljs Glad you could help her! Hopefully she’ll be fine….🙏

@ljs how can a human being can do that to their pets 😡