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It looks like GCC's naïveté about store-forwarding stalls is hurting its auto-vectorization strategy here. See also Store forwarding by example for some practical benchmarks on Intel with hardware performance counters, and What are the costs of failed store-to-load forwarding on x86? Also Agner Fog's x86 optimization guides.

(gcc -O3 enables -ftree-vectorize and a few other options not included by -O2, e.g. if-conversion to branchless cmov, which is another way -O3 can hurt with data patterns GCC didn't expect. By comparison, Clang enables auto-vectorization even at -O2, although some of its optimizations are still only on at -O3.)

It's doing 64-bit loads (and branching to store or not) on pairs of ints. This means, if we swapped the last iteration, this load comes half from that store, half from fresh memory, so we get a store-forwarding stall after every swap. But bubble sort often has long chains of swapping every iteration as an element bubbles far, so this is really bad.

(Bubble sort is bad in general, especially if implemented naively without keeping the previous iteration's second element around in a register. It can be interesting to analyze the asm details of exactly why it sucks, so it is fair enough for wanting to try.)

Anyway, this is pretty clearly an anti-optimization you should report on GCC Bugzilla with the "missed-optimization" keyword. Scalar loads are cheap, and store-forwarding stalls are costly. (Can modern x86 implementations store-forward from more than one prior store? no, nor can microarchitectures other than in-order Atom efficiently load when it partially overlaps with one previous store, and partially from data that has to come from the L1d cache.)

Even better would be to keep buf[x+1] in a register and use it as buf[x] in the next iteration, avoiding a store and load. (Like good hand-written asm bubble sort examples, a few of which exist on Stack Overflow.)

If it wasn't for the store-forwarding stalls (which AFAIK GCC doesn't know about in its cost model), this strategy might be about break-even. SSE 4.1 for a branchless pmind / pmaxd comparator might be interesting, but that would mean always storing and the C source doesn't do that.

If this strategy of double-width load had any merit, it would be better implemented with pure integer on a 64-bit machine like x86-64, where you can operate on just the low 32 bits with garbage (or valuable data) in the upper half. E.g.,

In order to achieve this goal we need to create permutation of all allowed paths. For example:

One of the prerequisites for using Discord.js v13 is that you need to use NodeJS v16.6 or higher (emphasis mine):

v13 requires Node 16.6 or higher to use, so make sure you're up to date. To check your Node version, use node -v

The fix is to update your node version, you can confirm your current node version by running node -v. There are a variety of different ways to update node, one way is to run the following commands if you're using Linux / iOS:

If a function only depends on other pure functions, then it is also pure. Since getPhoneNumberRules() just returns a fixed array, it's pure, so rules() is also pure.

But messages() calls getPhoneNumberMessage(), which calls the __() function that can return a different localized message if the location state changes, so it's not pure.

Not memory addressing, memory ordering. i.e. for lock-free atomics used for inter-thread synchronization - in x86, every asm load/store is acquire/release respectively. (With real x86 CPUs doing speculative early loads so performance doesn't suffer under normal conditions when a single thread is operating on memory that other threads aren't writing.)

M1 has hardware support for a mode like that, as well as a weakly-ordered mode to run native AArch64 code most efficiently. See

• https://singhkays.com/blog/apple-silicon-m1-black-magic/#performance-must-suck-when-trying-to-emulate-x86-on-arm-right
• https://www.reddit.com/r/hardware/comments/i0mido/apple_silicon_has_a_runtime_toggle_for_tso_to/.

And yes, https://github.com/saagarjha/TSOEnabler is open-source software to toggle that support. But it's a kernel extension, and code signing makes it tricky to get MacOS to allow it, and you have to sign it or disable signature verification or something:

Supposedly, you should be able to use this if you build and sign the kernel extension (disabling SIP if you aren't using a KEXT signing certificate) and drag it into /Library/Extensions. A dialog should come up to prompt you to enable the extension in the Security & Privacy preferences pane, you allow it from there and restart, and it will be installed. (If you're not seeing it, the permissions on the extension might be wrong: try a chown -R root:wheel.) In practice this can go wrong in many ways, and I have had luck by "resetting everything" and trying to install after doing the following:

[...] see the link for the list of steps

So yes, it's plausible that QEMU's x86 emulation could use the same hardware support that Rosetta-2's x86 emulation does. They're both x86 emulators.

And as you say, the main issue is Apple providing public APIs for enabling the HW mode so people don't have to install this kernel module manually; I'm sure most people wouldn't want to do that. I don't know much about the software situation, I was more interested in the CPU-architecture details.

Apparently, it may be a problem with the babel. Copy the folder @babel (specifically @babel/core) that is in the node_modules of a working project into the new project and it runs without problems.

It may be due to an update they did a couple of hours ago.

You can also remove the current @babel/core from the package.json and install this version npm install --save-dev @babel/core@latest.

Or use this:
@babel file: https://drive.google.com/file/d/1-z_4H_z4x075unZqZD41WYUwY_hsrKox/view.

Or replace the following codes in your package.json file then npm install.

This log was recently added in the Cloud Run data path to provide more context for debugging CloudSQL connectivity issues. However, the original logic was overly aggressive, emitting this message even for properly working CloudSQL connections. Your application is working correctly and should not receive this warning.

Thank you for reporting this issue. The fix is ready and should roll out soon. You should not see this message anymore after the fix is out.

You may try this function, your compiler should optimize this code for your CPU. It's not super perfect, but it should be relatively quick and mostly portable.

PS length should be divisible by 8 for max speed

One way you might work around this is to take advantage of the fact that static variables are, since C++11, initialised in a threadsafe way. Example: