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narrowbyte

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narrowbyte
·2 anni fa·discuss
the basic argument reads to me as "taxing wealth at 100% would be bad policy (for various reasons), therefore taxing wealth (at all) is fundamentally bad policy".

taxing income at 100% would also be bad policy - that fact alone doesn't mean that taxing income (at all) is fundamentally bad policy.

I don't find that the post really engages with any more realistic scenario.
narrowbyte
·2 anni fa·discuss
"Doesn't even try" is too strong.

"When compiling from the same source on independent infrastructure yields bit-by-bit identical results, this gives confidence that the build infrastructure was not compromised and the artifact really does correspond to the source." - https://reproducible.nixos.org/
narrowbyte
·2 anni fa·discuss
I intentionally said "more towards embarrassingly parallel" rather than "only embarrassingly parallel". I don't think there's a hard cutoff, but there is a qualitative difference. One example that springs to mind is https://github.com/simdjson/simdjson - afaik there's no similarly mature GPU-based JSON parsing.
narrowbyte
·2 anni fa·discuss
The post says, about SIMT / GPU programming, "This loss results from the DRAM architecture quite directly, the GPU being unable to do much about it – similarly to any other processor."

I would say that for SIMD the situation is basically the same. gather/scatter don't magically make the memory hierarchy a non-issue, but they're no longer adding any unnecessary pain on top.
narrowbyte
·2 anni fa·discuss
quite interesting framing. A couple things have changed since 2011

- SIMD (at least intel's AVX512) does have usable gather/scatter, so "Single instruction, multiple addresses" is no longer a flexibility win for SIMT vs SIMD

- likewise for pervasive masking support and "Single instruction, multiple flow paths"

In general, I think of SIMD as more flexible than SIMT, not less, in line with this other post https://news.ycombinator.com/item?id=40625579. SIMT requires staying more towards the "embarrassingly" parallel end of the spectrum, SIMD can be applied in cases where understanding the opportunity for parallelism is very non-trivial.