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"Performance Matters" by Emery Berger

Emery Berger explains why performance is hard to measure and deliver on modern hardware, showing how code layout and alignment can swamp optimization effects. He presents Stabilizer for statistically sound evaluation and Coz, a causal profiler.

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Why HN readers recommended it

It is the standard recommendation for anyone puzzled by unexplained benchmark changes from tiny code edits, and for learning about causal profiling.

This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.

Video & recommendation details

Creator / channel
Strange Loop Conference
Topic
performance measurement
Format
talk
Level
intermediate
HN recommenders in dataset
12
HN mentions in dataset
20
Recommendation years in dataset
2019–2025

These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.

From the original HN conversations

Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.

  • "Performance matters" by Emery Berger on StrangeLoop'19 is a great talk - [VIDEO] Also, rest of his talks are also fascinating: - [LINK] - [LINK]

    divan on Hacker News · 2019-12
    In Ask HN: Best Talks of 2019?

  • I haven't had a chance to mess around with it much, but the coz-profiler [1] uses basically the same idea, but the other way around (i.e., slow down everything else to get a "virtual speedup") which helps quantify what the effect of optimizing some code …

    jaybosamiya on Hacker News · 2020-01
    In Measure code execution time accurately in Python

  • Aside: this is the most amazing optimisation information I have seen: [VIDEO] Unfortunate that it is a video... Summary: Modern CPUs have so many hidden causes of performance variation, that you require special tools to actually measure small performance gains. He finds an amazing but …

    robocat on Hacker News · 2020-05
    In The naked truth about writing a programming language (2014)

Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.

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