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Hellishly Slow Level 13 Deflate Compression

kirill.korins.ky

21–29 of 29 posts

Re: Hellishly Slow Level 13 Deflate Compression

#21
post #16

OpenZL is the future: https://openzl.org/ "OpenZL delivers high compression ratios while preserving high speed, a level of performance that is out of reach for generic compressors. OpenZL takes a description of your data and builds from it a specialized compressor optimized for your specific format."

OpenZL is nice, but it's often less useful than you think - it requires that you know the structure of your data, and don't care about inspecting that data outside of your program. I've extracted one too many png files from a word document (by renaming .docx to .zip) to desire OpenZL everywhere... It might be better as a short-term "data in transit" compression than for long term storage.

Please check the OpenZL v0.2 + Silesia corpus benchmark.

  "OpenZL to offer 10% faster compression speed and 70% faster decompression speed compared to Zstandard level 1 on the Silesia corpus in our benchmarks."
  "OpenZL now ships its own LZ codec, exposed as ZL_GRAPH_LZ, and the serial profile in zli. It is still being actively developed to expand its feature set and improve performance on small inputs."
https://github.com/facebook/openzl/releases/tag/v0.2.0

Re: Hellishly Slow Level 13 Deflate Compression

#22
post #16

OpenZL is the future: https://openzl.org/ "OpenZL delivers high compression ratios while preserving high speed, a level of performance that is out of reach for generic compressors. OpenZL takes a description of your data and builds from it a specialized compressor optimized for your specific format."

The future may be ~ AI-assisted format detection + OpenZL

(~ OpenZL-AI-LLM recognises the data structure, then guides OpenZL toward the best lossless compression path )

Re: Hellishly Slow Level 13 Deflate Compression

#23
post #3
post #2

I love it. So much in computers is trade offs and this was a fun read exploring it. It would be interesting to see some economics of what 8,000% increase in encoding time takes to make that money back in terms of storage or bandwidth. I also wonder how brotli/lzma would compare here. Are there some obscene modes on those that had similar results?

zstd has higher level modes. Default is -3. I saw a good tradeoff between compression speed and ratio up to -9 or so. From -20 to -22 it will use much more memory and IIRC can have downstream effects on decompression speed. I'm using -9 for my container registry and plan to recompress at a higher level for commonly accessed base layers, as well as give customers a button that lets them pay a bit more to do it themsel…

Even compression level 1 or 2 is pretty good.

I once used https://github.com/google/riegeli and a low zstd compression level to store large quantities of protobuf data in an efficient manner (in terms of CPU, RAM and streaming to disk). Shame Riegeli is not well known, not well documented and does not have many tests.

Re: Hellishly Slow Level 13 Deflate Compression

#24
post #19
post #18

Earlier quoted context omitted.

Distant space probes are power constrained though. It's entirely possible the degradation of their RTG power sources would be more expensive doing the compression then just sending the data as is.

RTG degrade no matter what you do with the resulting heat. It doesn't matter if you compress stuff or just let them cpus idle be.

That's the point: you're going to spend a lot more time compressing when you could've just been sending data.

And you're eating into a limited overall power and weight budget to do rather then say, run the science on the probe.

Re: Hellishly Slow Level 13 Deflate Compression

#25
post #22
post #16

OpenZL is the future: https://openzl.org/ "OpenZL delivers high compression ratios while preserving high speed, a level of performance that is out of reach for generic compressors. OpenZL takes a description of your data and builds from it a specialized compressor optimized for your specific format."

The future may be ~ AI-assisted format detection + OpenZL (~ OpenZL-AI-LLM recognises the data structure, then guides OpenZL toward the best lossless compression path )

1. Upload data using conventional compression method (or uncompressed)

2. Spend orders of magnitude (literally) more on compute to run the LLM on the data than any compression algorithm would ever take.

Re: Hellishly Slow Level 13 Deflate Compression

#26
post #22

Earlier quoted context omitted.

The future may be ~ AI-assisted format detection + OpenZL (~ OpenZL-AI-LLM recognises the data structure, then guides OpenZL toward the best lossless compression path )

1. Upload data using conventional compression method (or uncompressed) 2. Spend orders of magnitude (literally) more on compute to run the LLM on the data than any compression algorithm would ever take.

[deleted]

Re: Hellishly Slow Level 13 Deflate Compression

#27
post #22
post #16

OpenZL is the future: https://openzl.org/ "OpenZL delivers high compression ratios while preserving high speed, a level of performance that is out of reach for generic compressors. OpenZL takes a description of your data and builds from it a specialized compressor optimized for your specific format."

The future may be ~ AI-assisted format detection + OpenZL (~ OpenZL-AI-LLM recognises the data structure, then guides OpenZL toward the best lossless compression path )

  "The unreasonable effectiveness of our first foray into training leads us to believe that the graph model is uniquely  positioned to facilitate ML-guided generation of compressors. We are tempted to view this as “the next big thing” in production-scale compression. Whereas compression research has up to now eluded those without domain expertise, we believe the future of application-specific compressors will be unlocked via investment in automated learning methods."
https://arxiv.org/abs/2605.09928 [11 May 2026] OpenZL: Using Graphs to Compress Smaller and Faster

Re: Hellishly Slow Level 13 Deflate Compression

#28
post #2

I love it. So much in computers is trade offs and this was a fun read exploring it. It would be interesting to see some economics of what 8,000% increase in encoding time takes to make that money back in terms of storage or bandwidth. I also wonder how brotli/lzma would compare here. Are there some obscene modes on those that had similar results?

I also wonder how brotli/lzma would compare here. Far better, just like anything else based on arithmetic coding. The main distinction here is that the output can still be decompressed with a standard Inflate implementation.

Except that brotli uses Huffman coding. It's main claim to fame is using higher order statistics to select a Huffman table and its built-in dictionary.

This class of compression programs sees larger differences due to the way the data is modelled instead of the specific entropy coder used.

Re: Hellishly Slow Level 13 Deflate Compression

#29
post #24
post #19

Earlier quoted context omitted.

RTG degrade no matter what you do with the resulting heat. It doesn't matter if you compress stuff or just let them cpus idle be.

That's the point: you're going to spend a lot more time compressing when you could've just been sending data. And you're eating into a limited overall power and weight budget to do rather then say, run the science on the probe.

What do you think the actual bandwidth speed on the voyager or new horizons is. You are spending lot of time sending the data anyway.
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