I signed up for an Oracle Cloud trial. They closed my trial a few days later and shut down my one trial VM without warning.
Weirdly they didn’t allow me to add payment info to continue. Even weirder their sales people kept contacting me asking me to come back. When I explained the situation they all tried to fix it and then went radio silent until the next sales rep came along to try to convince me to stay.
I searched Reddit at the time and a lot of other people had the same experience. A lot of other people were bragging about abusing their free tier and trials without consequences. I still don’t know how they decided to permanently close my account (without informing the sales team)
> My 4565p is a $500 cpu... 32 vcpus... racked in a datacenter. The machine cost under 2k.
> The cloud provider charging $140 / mo for 3x less vcpus you break even in a couple months, it doesn't matter if it dies a few months later
How do you calculate break even in a couple months if the machine costs $2,000 and you still have to pay colo fees?
If your colo fees were $100 month you wouldn’t break even for over 4 years. You could try to find cheaper colocation but even with free colocation your example doesn’t break even for over a year.
the 140/mo is for 3x less vcpu, so $420/mo savings if you use all those same cores. sorry for the poor comparison wording there. in a few months already up to $1300+ by 6 months already paid the machine.
colo fees are cheap if you need more than just 1u. even with a 50-100 fee you easily get way more performance and come ahead within a year
You originally said “a couple months” but now it’s 6 months and assumption of $0 collocation fees which isn’t realistic
In my experience situations rarely call for precisely 32 cores for a fixed period of 3 years to support calculations like this anyway. We start with a small set of cloud servers and scale them up as traffic grows. Today’s tooling makes it easy to auto scale throughout the day, even.
When trying to rack a server everyone aims higher because it sucks to start running into limits unexpectedly and be stuck on a server that wasn’t big enough to handle the load. Then you have to start considering having at least two servers in case one starts failing.
Racking a single self-built server is great for hobby projects but it’s always more complicated for serving real business workloads.
Don't nit-pick the "couple". It was used casually - like to mean not terribly long time. So the 2-6 spread, while technically big, is still just a trifle. While I'm nit-picking; up thread is talking about a limited box for CI and you're talking about scaling up real business workloads. That's just like the difference between 2 and 6. Give it a rest.
Everyone: run your scenarios and expectations in a spreadsheet and then use real data to run your CBA. Your case will be unique(ish) so make your case for your situation.
“It’s not X, it’s Y” is a common ChatGPT trope used to give a sense of depth to a statement but the specific contrast is generally murky like this. This Tweet was either written by ChatGPT or heavily influenced by ChatGPT style.
> I did my research in goodreads and started reading a trilogy that was highly rated. Holy crap it was so bad a quit about halfway through the second book. I went back to goodreads and the rating since my last visit had dropped drastically. A bot campaign or something fooled me, I guess.
Sites like Goodreads and Rotten Tomatoes are targeted by marketing firms.
Every popular outlet that become a proxy for reviews gets targeted. The New York Times best seller list has been gamed for decades by publishers who will mass-purchase their own books to get on to the list.
When getting a high score on Product Hunt was viewed as impressive it was standard practice for startups to have all of their friends and family register accounts and then have everyone spam their LinkedIn to beg for Product Hunt upvotes in a coordinated campaign. Now you can just buy Product Hunt upvotes for negligible prices from people in other countries who maintain hoards of sock puppet accounts. Anyone who posts to Product Hunt gets DMs from these companies offering their services. Nobody takes Product Hunt seriously now.
That's putting it mildly. I'm not normally about doing this sort of thing, but I went out of my way to find and install an extension to block google results for producthunt and alternative.to specifically.
> Much of it is operational necessity. But from a donor’s perspective, only 8 cents of every dollar shows up as direct aid and grants. The rest is invisible
One of my groups of friend groups has a lot of people who work at non-profits that are really dedicated to good causes. They are people who care and wanted to find jobs with purpose. The companies they work for aren’t, as far as I can tell, trying to grift or swindle.
Yet their overall efficiency looks a lot like this chart: Very little money makes it out of the program because it’s so expensive to pay for all of their staff, office space, and meta-activities like doing more fundraising.
From the outside looking in, there is a lot of malaise and inefficiency that just gets accepted at this level. They know they’re taking a pay cut relative to private industry so they, in turn, put in less effort. Many of them invite us to meet up in the afternoons because they’re “working from home” or just leaving the office early. Every time they encounter hard work the solution is to hire more people. Some of them switch to for-profit companies for a while before coming back to non-profits for the laid back working environment. It’s just accepted, to them, that non-profit means it doesn’t have to be efficient or a lot of work.
Maybe my second hand experience is unique to this little bubble I’m in, but whenever I see statistics like this I think it’s more normal than not.
Maybe I wasn’t clear, but even if they did put in 8 hour days they wouldn’t be close to the level of stress that we associate with burnout. This isn’t a self-protection measure so much as a lifestyle choice.
GeekBench probably made the right choice to optimize for more realistic real-world workloads than for the more specific workloads that benefit from really high core counts. GeekBench is supposed to be a proxy for common use case performance.
High core count CPUs are only useful for specific workloads and should not be purchased as general purpose fast CPUs. Unless you’re doing specific tasks that scale by core count, a CPU with fewer cores and higher single threaded throughput would be faster for normal use cases.
The callout against the poor journalism at Tom’s Hardware isn’t something new. They have a couple staff members posting clickbait all the time. Some times the links don’t even work or they have completely wrong claims. This is par for the site now.
To be fair, the Tom’s Hardware article did call out these points and the limitations in the article, so this SlashDot critique is basically repeating the content of the Tom’s Hardware article but more critically https://www.tomshardware.com/pc-components/cpus/apples-18-co...
Geekbench 6 Multi-Core is fundamentally a single-task benchmark. It measures performance in workloads, where the user is not running anything significant in the background. If you are a developer who wants to continue using the computer while compiling a large project in the background, Geekbench results are not particularly informative for you.
I've personally found that Apple's Pro/Max chips have already too many CPU cores for Geekbench.
> Furthermore, many of the suite’s multi-threaded subtests scale efficiently only to roughly 8 – 32 threads, which leaves much of such CPUs' parallel capacity idle, but which creates an almost perfect environment for Apple's CPUs that feature a relatively modest number of cores
Invalidates the entire comparison really, and should have canned the article if they had any integrity.
AMD has 16 cores, Apple has 18, Qualcomm has 18, Nvidia N1X has 20, and Intel has 24. All else being equal you actually want as few cores as you can get away with because that's less likely to be limited by Amdahl's Law. Arguably Intel/Nvidia CPUs are poorly designed and benchmarks have no obligation to accommodate them.
(I'm not counting high-end workstation/server CPUs because, as others in this thread have explained, Geekbench isn't intended for them.)
Right, this is a car-priced CPU and the only rational reason to have one is that you can exploit it for profit. One pretty great reason would be giving it to your expensive software developers so they don't sit there waiting on compilers.
Not sure you opened the blog post. The scaling is atrocious, even for tasks that should be extremely parallelizable. The Geekbench "Text Processing" benchmark supposedly processes 190 markdown files, and yet it tops at just 1.34x the single-thread performance when you have 4 cores, and it drops with more cores! I admit my expertise is algorithms & optimization so I may get more easily incensed by inept developers, but this is crazy... It is not realistic in any way, unless we assume the "real world" is just js beginners scribbling code for a website...
I think this actually concedes the main criticism.
If Geekbench 6 multicore is primarily a proxy for “common use case performance” rather than for workloads that actually use lots of cores, then it shouldn’t be treated as a general multicore CPU benchmark, and it definitely shouldn’t be the basis for sweeping 18-core vs 96-core conclusions.
That may be a perfectly valid design choice. But then the honest takeaway is: GB6 multicore measures a particular class of lightly/moderately threaded shared-task workloads, not broad multicore capability.
The criticism isn’t “every workload should scale linearly to 96 cores.” It’s that a benchmark labeled “multicore” is being used as if it were a general multicore proxy when some of its workloads stop scaling very early, including ones that sound naturally parallelizable.
Geekbench 6 isn't really marketed as a one-size-fits-all benchmark. It's specifically aimed at consumer hardware. The first paragraph on geekbench.com reads:
> Geekbench 6 is a cross-platform benchmark that measures your system's performance with the press of a button. How will your mobile device or desktop computer perform when push comes to crunch? How will it compare to the newest devices on the market? Find out today with Geekbench 6.
And further down,
> Includes updated CPU workloads and new Compute workloads that model real-world tasks and applications. Geekbench is a benchmark that reflects what actual users face on their mobile devices and personal computers.
The problem is, in practice, despite nonspecific marketing language, people do use the multicore benchmark to measure multicore performance. Including for things like Threadripper, which is not exactly an exotic science project CPU or non-personal or non-desktop.
> Including for things like Threadripper, which is not exactly an exotic science project CPU or non-personal or non-desktop.
We're talking about a CPU with a list price over $10000.
Geekbench 6 is a bad test to use to assess the suitability of a 96-core Threadripper for the kinds of use cases where buying a 96-core Threadripper might make sense. But Geekbench 6 does a very good job of illustrating the point that buying a 96-core Threadripper would be a stupid waste of money for a personal desktop and the typical use cases of a personal desktop.
> then it shouldn’t be treated as a general multicore CPU benchmark,
It is a general multi core benchmark for its target audience.
It’s not marketed as “the multi core scaling benchmark”. Geekbench is advertised as a benchmark suite and it has options to run everything limited to a single core or to let it use as many cores as it can.
>"High core count CPUs are only useful for specific workloads and should not be purchased as general purpose fast CPUs. Unless you’re doing specific tasks that scale by core count, a CPU with fewer cores and higher single threaded throughput would be faster for normal use cases."
I design multithreaded backends that benefit from as many cores as possible while not being a champion in a single core task. I think this is very common use case.
> The magic was that Apple brought the uncompromised experience to a laptop.
Apple’s power efficiency was a great bump forward, but the performance claims were a little exaggerated. I love my Apple Silicon devices but I still switch over to a desktop for GPU work because it’s so much faster, for example.
Apple had that famously misleading chart where they showed their M1 GPU keeping pace with a flagship nVidia card that misled everyone at launch. In practice they’re not even close to flagship desktop accelerators, unfortunately.
They have excellent idle power consumption though. Great for a laptop.
I also went from an Intel MacBook Pro to an M1 and appreciated it, but that leap was exaggerated by how bad the last few generations of Intel MacBook Pros were.
The Apple Silicon chassis was allowed to finally house an appropriate cooling solution, too. They are much quieter than the same Intel laptops when dissipating the same power levels.
> Even among researchers, people are a little superstitious about stuff like this.
Being superstitious is not common in the medical treatment world, where weird product names are common.
A doctor isn’t going to include the device’s brand name in their decision process for treating a cancer patient.
The Therac-25 case study is noted in the medical world but not to the same extent as in engineering. The case was a tragedy of bad engineering, but the doctors involved in directing the treatments were not at fault for the radiation over exposures.
The dubious idea is that eliminating private medical care systems would open up a world of research into treating very rare conditions with high R&D costs.
If this was true, why wouldn't all of the countries with socialized medicine be doing it already?
Weirdly they didn’t allow me to add payment info to continue. Even weirder their sales people kept contacting me asking me to come back. When I explained the situation they all tried to fix it and then went radio silent until the next sales rep came along to try to convince me to stay.
I searched Reddit at the time and a lot of other people had the same experience. A lot of other people were bragging about abusing their free tier and trials without consequences. I still don’t know how they decided to permanently close my account (without informing the sales team)
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