You can achieve close to the same thing using uBlock element zapper, without installing extra plugins. I use the same trick for SO ('Hot Network Questions' darkpattern) and other sites.
Ha, you're right. I should've used 30,000,000. The answer it gave regarding how to do "ties to even" was still correct though: "Evenness" is decided by the least significant bit of the mantissa, not be the "evenness" of the decimal representation.
Nice, that's simple enough! You may want to try talking to it via the API, last time I checked the web UI doesn't accept prompts >4K tokens while GPT-4 via the API has a 8K Token limit. And then there's the 32K version...
1. It can do some reformatting tasks faster than I can do them by hand. Example: Inline FuncA into FuncB <paste code for both functions>.
2. For more complicated tasks it requires good prompting. Example: Tell me three ways to fix this error, then pick the best way and implement it. <paste error> <paste relevant code>. Without the "step-by-step" approach it almost never works.
3. It's pretty good at writing microbenchmarks for C++. They always compile, but require some editing. I use the same prompting approach as (2.) for generating microbenchmarks.
4. It's pretty useful for explaining things to me that I then validate later via Google. Example (I had previously tried and failed to Google the answer): The default IEEE rounding mode is called "round to nearest, ties to even". However all large floating point numbers are even. So how is it decided whether 3,000,003 (which is not representable in fp32) becomes 3,000,002 or 3,000,004?.
5. It can explain assembly code. I dump plain objdump -S output into it.
The main limitation seems to be UI. chat.openai.com is horrible for editing large prompts. I wrote some scripts myself to support file-based history, command substitution etc.
Author here: Seems like a good trick! Though won't this affect shared memory alignment and make me loose those LDS.128 instructions? Or do these not require alignment? There's so little good docs on SASS.
In general I'm still confused about whether vectorized load instructions (LDS.128) necessarily lead to bank conflicts or not. My impression was that consecutive 32b floats get mapped to different banks, so to avoid conflicts I'd want the warp to load 32*32b consecutive elements at each step.