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Comment by omginternets | Hacker News Reader

Where does one go to learn all these optimization strategies and tactics? I really want to take a more deliberate approach to optimizing my (Go) code, but I’m currently stuck banging on things with a wrench between benchmarks.

Frustratingly, most advice I get is non-actionable, and amounts to restating general principles like “be aware of cache”. Are there any books or online resources that can help me build a more principled approach to runtime performance?

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The general process I’ve seen is to profile the application and look at what’s taking the most time. Then you sit down and think about how you could make the slowest parts faster. There isn’t a one-size-fits-all answer to your question. Benchmarks are good for validating your improvements, but not for finding what to improve. That’s what profiling is for.

Yeah; this is what I meant by “banging on things with a wrench between benchmarks”. I can’t fight the feeling that there is some background knowledge that makes the search more directed.

There is some background knowledge, like knowing time and space complexity of algorithms and datastructures that you use and how this abstractions interact with underlying hardware on which you are running your application. Knowing how CPU, CPU caches, OS memory management, as you mentioned that you work with Go so Go internals (like goroutines scheduling, how memory is allocated by Go runtime, how GC works etc), kernel task scheduling (context switching etc) work and how they impact your workload. A lot of it is intuition that you get with working with code that needs optimising throughout the years and a LOT of reading but sometimes you can flush that intuition into the toilet because you often find bottlenecks in places you wouldn't think about. So it really depends on the nature of your application (is it a network application or HPC, multi threaded? single threaded? distributed? you are optimising for high throughput or low latency, do you control hardware, network etc)

I've been similarly frustrated in the past.

Interestingly, I've found that studying other engineering disciplines outside of software engineering to be best. The best explanations and modeling frameworks for concurrency I learned were from network engineering books and a couple hardware design classes I took.

Re: principles around performance analysis and diagnostics, Brendan Gregg is a name you should look up. His book on systems performance is a tremendous resource in both principles and methodology. Even though it's not focused on coding specifically, the same principles apply.

Now that is a recommendation that I was not expecting, and which makes perfect sense in hindsight! Cheers! I shall order his book immediately.

> restating general principles like “be aware of cache”

It's a very powerful concept, and there really isn't all that much beyond it. That's the problem with pretty much all of the deep truths about computing, they're frankly pretty simple once you grok them.

But let's at least restate that well: https://www.youtube.com/watch?v=CSqbjfCCLrU https://www.youtube.com/watch?v=C6EWVBNCxsc

I’ll take it! Thanks for the links.

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