4 points

Maybe it’s time we invent JPUs (json processing units) to equalize the playing field.

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3 points

The best I can do is an ML model running on an NPU that parses JSON in subtly wrong and impossible to debug ways

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2 points

Just make it a LJM (Large JSON Model) capable of predicting the next JSON token from the previous JSON tokens and you would have massive savings in file storagre and network traffic from not having to store and transmit full JSON documents all in exchange for an “acceptable” error rate.

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2 points

Hardware accelerated JSON Markov chain operations when?

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1 point

You need to make sure to remove excess whitespace from the JSON to speed up parsing. Have an AI read the JSON as plaintext and convert it to a handwriting-style image, then another one to use OCR to convert it back to text. Trailing whitespace will be removed.

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1 point

Did you know? By indiscriminately removing every 3rd letter, you can ethically decrease input size by up to 33%!

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1 point
*

Latest Nvidia co-processor can perform 60 million curly brace instructions a second.

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1 point

CPU vs GPU tasks I suppose.

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1 point

GPU, render my 4.2 MB json file!

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1 point

Everybody gangsta still we invent hardware accelerated JSON parsing

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1 point

https://ieeexplore.ieee.org/document/9912040 “Hardware Accelerator for JSON Parsing, Querying and Schema Validation” “we can parse and query JSON data at 106 Gbps”

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0 points

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.

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1 point

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

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1 point

Well, do you have dedicated JSON hardware?

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2 points

Please no, don’t subsidize anything Java-Script. It will only make it less efficient.

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2 points

And thus JsPU was born from Lemmy

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1 point

Render the json as polygons?

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0 points

It’s time someone wrote a JSON shader.

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1 point

Ray TraSON

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