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Is it really the full pipeline running on Huawei hardware? That is training and inference?

The report only talks about validating the "fine-grained EP scheme" on Huawei hardware.


I don't think memory mirring features available today allow you to race two DRAM accesses and use the result that returns earlier?


The memory controller sends the read to the DIMM that is not refreshing. It is invisible to software, except for the side-effect of having better performance.


Mirroring is more of a reliability feature though, no? From my understanding it’s like RAID where you keep multiple copies plus parity so uncorrectable errors aren’t catastrophic. Makes sense for mainframes which need to survive hardware failures.

Refresh avoidance is a tangential thing the memory controller happens to be able to do in a scheme like that, but you’d really have to be looking at it in a vacuum to bill it as a benefit.

Like I said, it’s all about cache. You’re not going to DRAM if you actually care about performance fluctuations at the scale of refresh stalls.


Clearly, hitting a cache would be the better outcome. The technique suggested here could only apply to unavoidably cold reads, some kind of table that's massive and randomly accessed. Assume it exists, for whatever reason. To answer your question, refresh avoidance is an advertised benefit of hardware mirroring. Current IBM techno-advertising that you can Google yourself says this:

"IBM z17 implements an enhanced redundant array of independent memory (RAIM) design with the following features: ... Staggered memory refresh: Uses RAIM to mask memory refresh latency."


I can google, thanks. My point is that nobody is buying mainframes with redundant memory to avoid refresh stalls. It’s a mostly irrelevant freebie on hardware you bought for fault tolerance.


Do you have evidence that this is a fact? Have you looked at the computing requirements documents for, for example, stock exchanges? I have it on good evidence that stock exchanges ran on mainframes. They are essentially the counterparty (in a computing sense not a financial sense) in each placed order. If someone is willing to run a fiberoptic cable from Chicago to New York or New Jersey to exploit reduced propagation delay, admittedly much larger than a refresh stall, wouldn't you think that they or someone else would also be interested in predicting computing stalls. An exchange would face at least a significant reputational risk if it could be exploited that way.


The low latency matching engines in colos run Linux these days, and we use microwave instead of fiber. Incoming orders are processed by hardware receive timestamp, so predicting jitter doesn’t give you an advantage. Clearing and settlement I’m not sure about, not latency critical though, mainframes wouldn’t surprise me there.


If there's anywhere I don't want LLM slop it's probably my database system.


Shouldn't your snippet be using lzcnt? I can't see how this would result in the desired lookup.

for Zen5 rustc creates the following:

  utf8_sequence_length_lookup:
    shl edi, 24
    mov ecx, 274945
    not edi
    lzcnt eax, edi
    shl al, 2
    shrx rax, rcx, rax
    and al, 7
    ret
https://rust.godbolt.org/z/hz1eKjnaG


I can't see any elegant solution. \n

Struggling proc \n lzcnt ecx,ecx \n test cl,cl \n setz al \n lea edx,[ecx-2] ;[0,1,2] \n cmp rdx,2 \n cmovle eax,ecx \n ret \n Struggling endp


and the leading count comes in cl

We can assume the count has already been done.


Ah I can't read, thanks :-)


  After we implemented advanced bot traffic detection and filtering, their reported traffic plummeted by 71%. [...]
  But then the sales report came in. Their actual sales went up by 34%.
  Their real conversion rate optimization (CRO) efforts had been working all along, but the results were buried under an avalanche of fake clicks. They were not bad at marketing; they were just spending thousands of dollars advertising to robots programmed never to buy anything. Their marketing ROI went from "terrible" to "excellent" overnight.
I don't understand how detecting bot traffic would directly lead to less ad spend.

Can you just tell e.g. Google Ads that you don't want to pay for certain clicks?

Did they modify their targeting to try to avoid bots?


I could imagine that blocking bot traffic, would improve their retargeting and make sure that the retargeting budget is spent on real people leading to an increase in conversion.


What's the API here for Google Ads? How does their site report to Google Ads whether that was a good/bad user? Is this done through conversion tracking? If so, why would you track anything but a completed purchase in the first place?


I think Google calls it remarketing and it goes through Google Tag Manager. You can "tag" visitors how you want (duration, action, page scroll, etc.). It's just a javascript call to the API which you can trigger however you like.

You wouldn't necessarily want to track conversions for retargeting, since depending on your product or service, a second buy might be unlikely. But someone who checks out multiple product pages or articles on your site might be interested and buy in the near future. That of course are also actions bots could easily do.


If you building look-alike or remarketing audiences, having any bot users in there could give the wrong signal to Facebook or other platforms.

>Can you just tell e.g. Google Ads that you don't want to pay for certain clicks?

No


Sites send conversion events back to Google so they can target highly converting traffic.

If a bot network hits all the conversing events then Google will tailor the traffic to look more like the bot network.

If you filter the bot traffic out then Google can tailor the traffic to look like real converting users instead.


I assume it's the filtering - detect the user is a bot, don't even load the ads, etc?


As I understand it they are placing ads on other sites and are paying for visits to their site.


You didn't think through this did you

How would you do that on Google or a third-party site?


The author admits to it.

https://www.reddit.com/r/rust/comments/1mh7q73/comment/n6uan...

The reply to that comment is also a good explainer of why the post has such a strong LLM smell for many.


Yeah, I completely agree with that reply, thanks for the link.

BTW that Reddit post also has replies confirming my suspicions that the technical content wasn't trustworthy, if anyone felt like I was just being snobby about the LLM writing: https://www.reddit.com/r/rust/comments/1mh7q73/comment/n6ubr...


The easiest way to parallelize this RNG is to just run it in parallel on multiple states.


Do they help deter people from becoming smokers in the first place?


Not sure if much serious research has been put into it. I would be suspicious of it deterring them because a lot of initial smoking happens in social situations where friends pass out individual cigarettes.

By the time someone buys their own pack they are probably hooked.

I suspect the obscene taxes blocking out young folks is one of the most effective strategies


I doubt that this is a problem in need of a technical solution. In any case, this system can easily be circumvented by emulating the key presses on that website.


Looking at a few files, there's definitely some generated comments in there. Do you have any method to quantify how much of it is (likely) generated?


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