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I have no dog in this fight, but feel compelled to defend the authors here. Recursion does not test compute, rather it tests the compiler's/interpreter's efficiency at standing up and tearing down the call stack.

Clearly this language is positioned at using the gpu for compute-heavy applications and it's still in its early stages. Recursion is not the target application and should not be a relevant benchmark.



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Okay, no. I know I called out performance in my post, but that was just from my observations. It surprised me to see something be that much slower than pure python. If you show me a near-python code example in a new language, as someone who mostly writes python code, I'm going to go and write it in python and see how it compares performance wise.

The authors never made any kind of false claims at all. You're reading a lot in to both their README and my post.

They've updated the README for a bit of clarity, but even re-reading the README as it was when I looked this morning (and even a few from before) it hasn't claimed to be fast. The claims are all related to the features that it does have, around parallelisation.


Where did he claim it is fast? As far as I can see the only claim is that it scales linearly with cores. Which it actually seems to do.


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I'll give you the benefit of the doubt in case README changed, but here's the benchmark it claims, currently, against it's own execution modes:

CPU, Apple M3 Max, 1 thread: 12.15 seconds

CPU, Apple M3 Max, 16 threads: 0.96 seconds

GPU, NVIDIA RTX 4090, 16k threads: 0.21 seconds

The README mentions "fast" in 2 places, none of which is comparing to other languages.


You're missing some context, it's not bitonic sort itself that would present an issue with GPUs, it's the "with immutable tree rotations" part, which in a naive implementation would imply some kind of memory management that would have trouble scaling to thousands of cores.


Yes and those benchmarks are real. Showing linear speed up in the number cores when writing standard code is a real achievement. If you assumed that somehow means this is a state of the art compiler with super blazing performance is on no one but you. The readme lays it out very clearly.


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the irony in you blasting all over this thread is that you dont know how it even works. You have 0 idea if their claims of scaling linearly are causing bottlenecks in other places as you state, if you read actual docs on this its clear that the actaul "compiler" part of the compiler was put on the backburner while the parallellization was figured out and as that is now done a bunch of optimizations will come in the next year


If you want to bring up CS101 so badly, surely turing machines and lambda calculus would be more relevant.

The actually interesting claim is that somebody has found a practical use for Interaction Combinators as a computing model for putting GPUs to work.




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