If you’re not aware, it was called MB because of JEDEC when IEC units weren’t invented. IEC units were introduced because they remove the double meaning of JEDEC units — decimal and binary. IEC units only carry the binary meaning, hence why they’re superior. If you convert 1000 kB to 1 MB then use MB, but in case of 1024 KiB to 1 MiB you should be using MiB. It’s all about getting the point across, and JEDEC units aren’t good at it.
I’m failing to understand why we would need decimal units at all. Whats the point of them? And why do the original units havr to change name to something as ridiculous as “Gibibyte” while the unnecessary decimal units get the binary’s old name?
You poor innocent soul… I can try to explain why decimal is even mentioned, but it would probably take a lot of time, and I’m not sure if I will be able to clarify things up.
I can at least say this: 2 TB HDD drive is indeed 2*10^12 B, but suddenly shindow$ in its File Explorer will show you that in fact the drive is only 1.82 TB. But WHY? Everyone asks, feeling scammed. Because HDD spec uses decimal units (SI; MB) and Window$ uses binary units (JEDEC; MB), i.e., 1.82 TiB (IEC; MiB). And macOS also uses JEDEC units, AFAIK.
More and more FOSS software uses IEC units and KDE Plasma is a good example: file manager, package manager etc. uses IEC units. Simply put, JEDEC added the binary meaning to decimal units, so at first MB (and now) only carried decimal meaning (until JEDEC shit out their standard). And the only reason why “gibibyte” is ridiculous, is because we all grew up with JEDEC interpretation of SI units. So it will take many generations for everyone to adapt xxbityte words into daily conversations. I’m (already) doing my part. It’s just the legacy that we have to deal with.
All international bodies (BIPM, NIST, EU) agree that the SI prefixes “refer strictly to powers of 10” and that the binary definitions “should not be used” for them.
What is bad about it? It wasn’t an offensive statement, it was stating the fact that that the person was new to the whole “MB vs. MiB” mega story that is an ongoing issue for at least over 10 years, and that I envy/pity the “cruel world that they are in” (where everyone uses JEDEC units while IEC ones should be used instead).
If that is the only reason why you’re starting calling names other people and downvoting all of their comments then you’re overreacting. The person I talked with didn’t even mention it. I heard this phrase from some movie or something.
The last part was wrapped in a spoiler and under the post scriptum clause to indicate that it’s not important and that you should really see it if you don’t want to. And I added that just to educate a bit more, since I already started the " this is wrong and this is right" conversation. To be honest, I hate that that OS had so many naming changes that everyone is just left confused in the end. Some still say OS X or whatever else.
Well, thank you for taking the time to write this detailed explanation!
Windows and MacOS use the abbriviation “MB” referring to the binary units, correct? How come that these big OS’s use another unit than these large international bodies recognize?
On a side note, I’ve always found it weird why HDDs or SSDs are/were sold with 128GB, 265GB, 512GB etc. when they are referring to decimal units.
Windows and MacOS use the abbriviation “MB” referring to the binary units, correct?
Yez. I’m only sure about the first one, but didn’t test myself whether the macOS is using power of 2 or 10 under the hood (of MB). You can open properties of something big and try converting raw number of bytes with /1024^n and /1000^n and compare the end results.
How come that these big OS’s use another unit than these large international bodies recognize?
Legacy, legacy everywhere (IMO). And of course they don’t want to confuse their precious users that don’t know any better. And this also would break some scripts that rely on that specific output. GNU C library also uses JEDEC units by default, hence flatpak and other software.
On a side note, I’ve always found it weird why HDDs or SSDs are/were sold with 128GB, 265GB, 512GB etc. when they are referring to decimal units.
It is weird for everyone, because we mainly only count with multiples of 2 when it comes to digital size of information. I didn’t investigate why they use power of 10, but I’ve seen that some other hardware also uses decimal units (I think at least in RAM, but JEDEC is used intentionally or not for CPU cache memory). I had a link where the RAM thingy is lightly addressed, but I couldn’t find it.
As far as my understanding goes, Zed uses the GPU only for rendering things on screen. And from what I’ve heard, most editors do that. I don’t understand why Zed uses that as a key marketing point
That’s not how this works, GPUs are fast because the kind of work they do is embarrassingly parallel and they have hundreds of cores. Loading a json file is not something that can be trivially parallelized. Also, zed use the gpu for rendering, not reading files.
I’d like to point out for those who aren’t in the weeds of silicon architecture, ‘embarrassingly parellel’ is the a type of computation work flow. It’s just named that because the solution was an embarrassingly easy one.
Huh, I was about to correct you on the use of embarrassment in that the intent was to mean a large amount, but it seems a Wiki edit reverted it to your meaning a year ago, thanks for making me check!
I’ve accidentally opened enormous single line json files more than once. Could be lsp config or treesitter or any number of things but trying to do any operations after opening such a file is not a good time.
I have the same problem with XML too. Notepad++ has a plugin that can format a 50MB XML file in a few seconds. But my current client won’t allow plugins installed. So I have to use VS Code, which chokes on anything bigger than what I could do myself manually if I was determined.
Personally, now that I have a machine capable of running the toolchains, I want to explore hardware accelerated compilation. Not all steps can be done in parallel but I bet a lot before linking can.
ieeexplore.ieee.org/document/9912040“Hardware Accelerator for JSON Parsing, Querying and Schema Validation” “we can parse and query JSON data at 106 Gbps”
They get to this result on 0.6 MB of data (paper, page 5)
They even say:
Moreover, there is no need to evaluate our design with datasets larger than the ones we have used; we achieve steady state performance with our datasets
This requires an explanation. I do see the need - if you promise 100Gbps you need to process at least a few Tbs.
Imagine you have a car powered by a nuclear reactor with enough fuel to last 100 years and a stable output of energy. Then you put it on a 5 mile road that is comprised of the same 250 small segments in various configurations, but you know for a fact that starts and ends at the same elevation. You also know that this car gains exactly as much performance going downhill as it loses going uphill.
You set the car driving and determine that, it takes 15 minutes to travel 5 miles. You reconfigure the road, same rules, and do it again. Same result, 15 minutes. You do this again and again and again and always get 15 minutes.
Do you need to test the car on a 20 mile road of the same configuration to know that it goes 20mph?
JSON is a text-based, uncompressed format. It has very strict rules and a limited number of data types and structures. Further, it cannot contain computational logic on it’s own. The contents can interpreted after being read to extract logic, but the JSON itself cannot change it’s own computational complexity. As such, it’s simple to express every possible form and complexity a JSON object can take within just 0.6 MB of data. And once they know they can process that file in however-the-fuck-many microseconds, they can extrapolate to Gbps from there
Based on your analogue they drive the car for 7.5 inches (614.4 Kb by 63360 inches by 20 divided by 103179878.4 Kb) and promise based on that that car travels 20mph which might be true, yes, but the scale disproportion is too considerable to not require tests. This is not maths, this is a real physical device - how would it would behave on larger real data remains to be seen.
Except we know what the lifecycle of physical storage is, it’s rate of performance decay (virtually none for solid state until failure), and that the computers performing the operations have consistent performance for the same operations over time. And again, while for a car such a small amount can’t be reasonably extrapolated, for a computer processing an extremely simple format like JSON, when it is designed to handle FAR more difficult tasks on the GPU involving billions of floating point operations, it is absolutely, without a doubt enough.
You don’t have to believe me if you don’t want but I’m very confident in my understanding of JSON’s complexity relative to typical GPU workloads, computational analysis, computer hardware durability lifecycles, and software testing principles and best practices. 🤷
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