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anp
lolbench
Rust2018–2018
anp / lolbench

lolbench

tracking performance of rustc-generated binaries over time

2Distinct people
3Mentions
0Explicit recommenders
103GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

tracking performance of rustc-generated binaries over time

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by hour3 dated mentions

Observed mentions: 2018-10-01 20:28:58 UTC to 2018-10-02 02:56:09 UTC.

012018-10-01 20:00:00 UTC to 2018-10-01 21:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsOct 1, 20:002018-10-01 21:00:00 UTC to 2018-10-01 22:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-10-01 22:00:00 UTC to 2018-10-01 23:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-10-01 23:00:00 UTC to 2018-10-02 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsOct 1, 23:002018-10-02 00:00:00 UTC to 2018-10-02 01:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-10-02 01:00:00 UTC to 2018-10-02 02:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-10-02 02:00:00 UTC to 2018-10-02 03:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsOct 2, 02:00

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Oct 1, 20:002018-10-01 20:00:00 UTC2018-10-01 21:00:00 UTC101
Oct 1, 21:002018-10-01 21:00:00 UTC2018-10-01 22:00:00 UTC000
Oct 1, 22:002018-10-01 22:00:00 UTC2018-10-01 23:00:00 UTC000
Oct 1, 23:002018-10-01 23:00:00 UTC2018-10-02 00:00:00 UTC101
Oct 2, 00:002018-10-02 00:00:00 UTC2018-10-02 01:00:00 UTC000
Oct 2, 01:002018-10-02 01:00:00 UTC2018-10-02 02:00:00 UTC000
Oct 2, 02:002018-10-02 02:00:00 UTC2018-10-02 03:00:00 UTC101

What Hacker News says

3 sources
I talked about this a little bit in the meetup talk I linked and I intend to write a bit more about this, but I'll try to summarize. There are kind of three prongs here: First, using criterion.rs does a ton for giving us more stable metrics. It handles things like warmups, accounting for obvious statistical outliers in the sample runs, postprocessing the raw data to provide more meaningful statistics, etc. I'm currently using a fork of the library which additionally does this recording and processing of a variety of metrics we get from `perf_event_open` on Linux but which I assume you could get through ETW or Intel/AMD's userspace PMC libraries. Second, I try to provide a stable environment so that results over long time deltas are comparable and we can store the data for offline analysis rather than having to checkout recent prior commit
Read the rest
s and compare the current PR/nightly/etc against them. Prior to the current deployment I was using cgroups to move potentially competing processes off of the benchmark cores which produced some nice results. However I had some issues with the version of the cpuset utility I installed on the debian machines and I haven't sorted it out yet. Third, we do a few things with the time-series-esque data we get from measuring multiple toolchains to try and only surface relevant results. Those are mostly in src/analysis.rs if you want to poke around. It basically boils down to calculating the Kernel Density Estimate of the current toolchain's value being from the same population (I hope these terms are halfway correct) as all prior toolchains' value. I hope that with a few extensions to the above we can get close to being reliable enough to include in early PR feedback, but I think the likely best case scenario is a manually invoked bot on PRs followed by me and a few other people triaging the regressions surfaced by the tool after something merges. Here are a few issues that I think will help improve this too: https://github.com/anp/lolbench/issues/20 https://github.com/anp/lolbench/issues/17 https://github.com/anp/lolbench/issues/14
In Lolbench: automagically and empirically discovering Rust performance regressions

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