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andikleen
pmu-tools
Python2014–2025
andikleen / pmu-tools

pmu-tools

Intel PMU profiling tools

6Distinct people
11Mentions
0Explicit recommenders
2.3KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Intel PMU profiling tools

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 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 4:00:59 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 year11 dated mentions

Observed mentions: 2014-05-13 20:11:34 UTC to 2025-08-16 23:06:03 UTC.

0122014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments20142015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025

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
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC202
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC101
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC211
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC101
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC101
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC101
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC101

What Hacker News says

1 sources
> 5-10% performance boost sounds huge. Wouldn't we have much larger TLBd if page walk was really this expensive? It's pretty typical for large programs to spend 15+% of their "CPU time" waiting for the TLB. [1] So larger pages really help, including changing the base 4 KiB -> 16 KiB (4x reduction in TLB pressure) and using 2 MiB huge pages (512x reduction where it works out). I've also wondered why the TLB isn't larger. > On the other hand 9% increase in memory usage also sounds huge. How did this affect memory usage that much? This is the granularity at which physical memory is assigned, and there are a lot of reasons most of a page might be wasted: * The heap allocator will typically cram many things together in a page, but it might say only use a given page for allocations in a certain size range, so not all allocations will snuggle in
Read the rest
next to each other. * Program stacks each use at least one distinct page of physical RAM because they're placed in distinct virtual address ranges with guard pages between. So if you have 1,024 threads, they used at least 4 MiB of RAM with 4 KiB pages, 16 MiB of RAM with 16 KiB pages. * Anything from the filesystem that is cached in RAM ends up in the page cache, and true to the name, it has page granularity. So caching a 1-byte file would take 4 KiB before, 16 KiB after. [1] If you have an Intel CPU, toplev is particularly nice for pointing this kind of thing out. https://github.com/andikleen/pmu-tools
In Adding 16 kb page size to Android

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