voidstarcpp

>But if our performance knowledge is outdated, how do we know which cases to separate the code into?

Case separation is less of a commitment than deciding on the specific optimization yourself. You know empirically which cases are used in your application and can separate those to see if there's a benefit without any manual optimization knowledge, like I did in the image scaling example, without having much of a theory in mind as to why it might be faster.

The "tiny math function" is used for expository purposes of the generic application, to fit a trivial example on one page. Obviously it's not how you would literally write a function that transforms elements in a vector.

>GCC is actually good at that, -O3 has no issue recognizing it.

imo, if you have to go to O3 or enable a pragma to get an "obvious" optimization then this is undesirable and probably something the programmer still needs to be conscious of, especially since we spend so much time doing development builds that are not at the maximum release optimization level.

Addressing the aliasing concern would be the easiest improvement. I observed in the assembly that the source pixel is being re-read all four times it is used, which could be fixed.

Writing an optimal composite function is of course not really the goal, nor of much educational/entertainment value. For any additional speed I already have a function which slices up compositing tasks into chunks and puts them on a thread pool.

This is possible if the call site can see the implementation, but you can't count on it for separate translation units or larger functions.

My goal was to not rely on site-specific optimization and instead have one separately compiled function body that can be improved for common cases. Certainly, once the compiler has a full view of everything it can take advantage of information as it pleases but this is less controllable. If I were really picky about optimizing for each use I would make it a template.

>Doesn't even need the `inline` keyword for this at `-O2`

The inline keyword means little in terms of actually causing inlining to happen. I would expect the majority of inlining compilers do happens automatically on functions that lack the "inline" keyword. Conversely, programmers probably add "inline" as an incantation all over the place not knowing that compilers often ignore it.

You need to use a compiler specific "always inline" directive if you want macro-like functionality of actually inlining code.

On its own, the C++ "inline" keyword does not cause inlining to happen, although compilers may treat it like a hint depending on optimization level. GCC does not inline an "inline" function on O0.

"Inline" in the C++ standard means "multiple definitions permitted" so the same entity can exist in multiple translation units without upsetting the linker. This is why C++17 added "inline" variables, which can be initialized in a header that's included in multiple places, even though the inlining concept has no applicability to a variable. The keyword was adopted for this purpose because of the primary association with affecting linkage behavior.

TL;DR: If you copy paste the same implementation code in different branches, you give the compiler opportunities to generate faster code for each case it wouldn't have otherwise generated, without you having to do any manual optimization work.

In my limited experiments WAL wasn't faster for high-row-speed writes.

When rows/s are maximized SQLite is CPU limited by internal bytecode operations rather than waiting for disk stuff.

PostgreSQL supports heap tables, which should blow away SQLite's mandatory clustered index tables in an unindexed insert test.

With SQLite by default nobody else can even read the database while it's being written, so your comment would be better directed to a conventional database server.

>Parsing the very simple SQL doesn't seem like it would account for much time, so is the extra time spent redoing query planning or something else?

If you're inserting one million rows, even 5 microseconds of parse and planning time per query is five extra seconds on a job that could be done in half a second.