narrowbyte

Joined 3 years ago

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Aug 2

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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.

Comment · 2 years ago

"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/

Comment · 2 years ago

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.

Comment · 2 years ago

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.

Comment · 2 years ago

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.

Comment · 3 years ago

what does this mean? "In LLVM IR, much like in Rust but unlike in C/C++, individual loads and stores are volatile (i.e., have compiler-invisible side-effects)."