31–40 of 153 posts
In my experience most webapps can fix so much low hanging performance issues by mapping the API in a way that matches how its used in the client. It can remove so much mapping and combining for data all over.
Good article that I agree with mostly. One interesting note is this: > There is no way to provide both optimized assembly and equivalent C code and let the compiler use the former in the general case and the latter in special cases. This is true, but can be seen as a failure of language and tooling. For example, Halide [1] pioneered (AFAIK) the concept of separating algorithm from implementation at the language level…
> Halide [1] pioneered (AFAIK) the concept of separating algorithm from implementation at the language level. you don't need to go all the way to Halide to do what the article is claiming isn't possible - you can do it just by including a "micro-kernel" in your library and have the code branch to that impl (depending on something at runtime) instead of whatever the C code compiled down to. this is done every single d…
The fact that sometimes optimization work is tricky or requires some pre-thinking, or is even gasp counter-intuitive is such a hilarious way to say "this is hard". That's just table stakes starting points for so-so-so much work.
Edit: Heck, even deciding whether to prioritize optimization work or feature work is usually a harder problem than the actual optimization work itself.
I've since noticed this many times. Optimizing is like meditation to me. It's very mechanical (measure), with a sprinkle of creative work (once you know what is slow, it's quite obvious how to make it faster, but just challenging enough to be engaging), and it has a very nice tight feedback loop: Something is slow. I make a change. Now it's fast. Next.
Optimizing is my happy place.
> I dislike the “intuition doesn’t work, profile your code” mantra because it seemingly says profiling is a viable replacement for theoretical calculations, which it isn’t. This seems like a nonsensical statement to me. How could measuring be a substitute for thinking/analyzing/predicting/forming a plan? Measuring/profiling just means observing the system you want to optimize in a systematic way. You certainly won't…
I think what he’s saying here is you can’t skip the basic math step to arrive at good performance. Staring at profiling results will lead you to a local minima
I once had this kind of body recovery/stress level measuring thingy on me for a few days, and a doctor would then analyze my health and such. I was under some stress those days and (according to the measurements) I wasn't recovering properly even during the nights. But then there was this one, long, flat, deep green curve in the middle of my work day. I checked from my VCS what I was doing during that period: I was o…
Unfortunately I had to give up when I was still 10 times slower than the reference lol
> I dislike the “intuition doesn’t work, profile your code” mantra because it seemingly says profiling is a viable replacement for theoretical calculations, which it isn’t. This seems like a nonsensical statement to me. How could measuring be a substitute for thinking/analyzing/predicting/forming a plan? Measuring/profiling just means observing the system you want to optimize in a systematic way. You certainly won't…
I think what he’s saying here is you can’t skip the basic math step to arrive at good performance. Staring at profiling results will lead you to a local minima
Earlier quoted context omitted.
I think what he’s saying here is you can’t skip the basic math step to arrive at good performance. Staring at profiling results will lead you to a local minima
Well, he's saying that intuition does work... But does it really? If a problem area is so intuitively obvious, why would you introduce the problem in the first place? In reality, performance optimizations are usually needed where you least expect them. Which means that you can't get there intuitively. Hence, the suggestion of using profiling to help track down where the problem is instead.
Pretty much everyone I know will throw down an O(n^2) algorithm or whatever in their first pass and replace it with something more thought out once they have the time to think deeply about it.
If you're fretting about optimization at every stage of development, you're really doing it wrong. This is precisely the type of early optimization that everyone and their dog will tell you is bad. You should focus first on making your program work and laying out the logic and data flows. Optimization does not matter until the program is almost finished.
I once had this kind of body recovery/stress level measuring thingy on me for a few days, and a doctor would then analyze my health and such. I was under some stress those days and (according to the measurements) I wasn't recovering properly even during the nights. But then there was this one, long, flat, deep green curve in the middle of my work day. I checked from my VCS what I was doing during that period: I was o…
Earlier quoted context omitted.
I think what he’s saying here is you can’t skip the basic math step to arrive at good performance. Staring at profiling results will lead you to a local minima
Well, he's saying that intuition does work... But does it really? If a problem area is so intuitively obvious, why would you introduce the problem in the first place? In reality, performance optimizations are usually needed where you least expect them. Which means that you can't get there intuitively. Hence, the suggestion of using profiling to help track down where the problem is instead.
Bring in a performance expert and their intuition can quickly identify many performance improvements. The tough part for the business is when and where do you pay for the experience of performant code, and when is good enough to leave alone?